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Wechselsprungkonstruktion

For interactive reading and executing code blocks Binder, or install Python and JupyterLab locally to run hydraulic-jump.ipynb on your own machine.

Diese Übung ** orientiert sich am Clyde Dam, am Clutha River / Mata-Au in Central Otago, ist Neuseelands größter Beton-Schwerkraftdamm: 490 m breit, bis zu 60 m hoch über dem alten Flussbett und beschlagnahmender Lake Dunstan. Seine gated Überlauf hat vier radiale Tore, jeweils 15 m hoch und 10 m breit, entworfen, um eine Entladung von 3200 m3^3s (0,2% AEP) auf einem Seehöhe von 195.1 m zu führen. Das Wasser, das den Überlauf passiert, steigt eine Rutsche auf der Dammseite ab. Der hochenergetische Fluss an der Zehe dieser Rutsche muss in einem Tosbecken abgeführt werden, damit das Flussbett stromabwärts nicht durchgeschwemmt wird.

Schülerherausforderung: Größe der Beckengeometrie, so dass sich der Wechselsprung innerhalb des Beckens bildet und dort gehalten wird, und dadurch das Durchforsten stromabwärts des Damms vermieden wird.

Struktur der Berechnungsvorlage

Übersicht

Wer macht die Arbeit? |----------- | I Der Fluss, der am Becken ankommt: Entladung der Einheit, Energiekopf an der Rutsche und der Tiefe des Schwanzwassers | **gegeben ** - führen Sie die Zellen und lesen Sie die Ergebnisse | | II | Tosbecken & Wechselsprungdesign | student -- Workflow ist gegeben, Wechselsprunggleichungen müssen eingegeben werden |

Einzelheiten

Teil I legt die Größen fest, auf die der Wechselsprung und damit das Becken ausgelegt ist: die Entladung QQ und die Einheitsentladung qq, der Energiekopf H0H_0 oberhalb des unversenkten Beckens invertiert und die Schwanzwassertiefe htwh_{tw} erhalten aus der Manning-Gleichung.

Part II contains three short functions, marked Task 1 to Task 3. Each is a single equation from the lecture. The numerics around them, that is the root finding, the search over the basin depth and the plots, are given, so that an incorrect equation produces an incorrect number rather than a traceback. The equation at the centre of the exercise is the sequent-depth (Bélanger) equation of Task 2; the other two establish the state it is applied to and the criterion by which the result is judged. On completing Part II you should be able to:

  • die Energie-, Kontinuitäts- und Impulsverhältnisse ausdrücken, die einen Wechselsprung als Code festlegen;

  • Bestimmen, ob ein bestimmter Unterwasserspiegel einen Wechselsprung in einem Becken behält oder stromabwärts streicht;

  • die Tiefe, die Länge und den Scheuerschutz eines Beckens vor diesen Beziehungen zu bestimmen.

Notation

Tiefen werden als hh bezeichnet und Köpfe HH, in der Vorlesung und hier gleichermaßen. Der Retentionsgrad wird als rtr_{\mathrm{t}} und nicht als ε\varepsilon des deutschen Arbeitsbeispiels bezeichnet, aus dem dieser Workflow angepasst wird, da ε\varepsilon die turbulente Dissipationsrate in der Vorlesung bezeichnet.

| Symbol | Bedeutung | Einheit | |----------- | QQ | spillway design flow | m3^3s | | ww | Breite des Tosbeckens | m | | wtww_{tw} | Tailwater River Breite | m | qq | Entladung pro Einheitsbreite, q=Q/wq = Q/w | m2^2/s | | H0H_0 | Energie Kopf über dem unversenkten Becken invertiert | m | | db\mathbf{d_b} | Tiefe des Beckenbodens unter dem flussabwärts gelegenen Bett | m | | HH | Energie Kopf über dem Beckenboden, H=H0+dbH = H_0 + \mathbf{d_b} | m | | h1h_1, v1v_1, Fr1Fr_1 | Tiefe, Geschwindigkeit und Froude-Zahl am Eingang des Beckens (überkritisch) | m, m/s, -- | | h2h_2 | konjugierte (sequente) Tiefe des Wechselsprungs | m | | htwh_{tw} | Schwanzwassertiefe im flussabwärts gelegenen Bereich | m | | nMn_M | Manning Rauheitskoeffizient der Downstream-Reichweite | s/m1/3^{1/3} | rtr_{\mathrm{t}} | Retention Ratio, (htw+db)/h2(h_{tw} + \mathbf{d_b})/h_2 | -- | | S0,twS_{0,tw} | Längsbettneigung des stromabwärts gelegenen Bereichs | -- | | ΔH\Delta H | Kopfverlust über den Wechselsprung | m | | flf_{l} | Peterka Basin-Längen-Multiplikator, gelesen von Fr1Fr_1 | -- | | lbl_b, lsl_s | Beckenlänge und Scheuerschutzlänge | m |

Die folgende Zelle importiert die Python-Pakete und die für die Figuren verwendeten Farben. Diese Zellen dienen der Funktionsweise der Berechnungsvorlage und tragen keine Lerninhalte.

import math
from dataclasses import dataclass

import matplotlib.patheffects as pe
import matplotlib.pyplot as plt
import numpy as np
from scipy.optimize import brentq

# Physical constants used throughout.
G = 9.81  # gravitational acceleration [m/s2]

# The lecture palette, so that figures and slides read as one piece.
NAVY, BLUE, CYAN, GREEN, WARN, GREY = (
    "#0C0C48", "#00467F", "#00CAEF", "#167D61", "#C74B2A", "#4A4A4C",
)

plt.rcParams.update({
    "figure.figsize": (8.4, 4.2),
    "figure.dpi": 110,
    "axes.spines.top": False,
    "axes.spines.right": False,
    "axes.titleweight": "bold",
    "axes.labelcolor": NAVY,
    "axes.edgecolor": NAVY,
    "text.color": NAVY,
    "xtick.color": NAVY,
    "ytick.color": NAVY,
    "font.size": 9,
})

Part I: boundary conditions for the hydraulic jump design

Everything in this part is given. Run the cells and note the quantities passed on to Part II. No hydraulic-jump calculation is performed here.

Note: only the discharge, the associated lake level and the gate dimensions are published figures; the remainder are stated assumptions. The real structure is not this simple. A gate-controlled sluice rated at 1500 m3^3/s adjoins the spillway, and the two together pass the largest anticipated flood of 6820 m3^3/s. The energy dissipation at the toe was developed on physical models by the Ministry of Works and Development rather than from a closed-form calculation. This exercise therefore represents the first step that engineers typically complete before a detailed design study with physical or numerical models; it is not a substitute for such a study.

quantityvalueremark
QQ, spillway design flow3200 m3^3/spublished, at a lake level of 195.1 m
ww, width of the chute and basin40 mfour 10 m gate bays, idealised as one rectangular chute with the piers ignored
H0H_0, energy head above the un-sunk basin invert50.00 massumed: the design flood level stands approximately 60 m above the riverbed, of which some 10 m is taken as lost down the chute
wtww_{tw}, nMn_M, S0,twS_{0,tw} of the Clutha downstream of the dam60 m, 0.045 s/m1/3^{1/3}, 0.0006assumed

In New Zealand practice, catchment design floods are quoted as an annual exceedance probability, so the 100-year flood is the 1% AEP event and the 500-year flood quoted for Clyde is the 0.2% AEP event; the older average recurrence interval (ARI) denotes the same thing. A dam spillway, however, is not designed to a catchment AEP at all: under the NZSOLD New Zealand Dam Safety Guidelines the inflow design flood follows from the dam’s Potential Impact Classification, and for a high-consequence dam it extends to the probable maximum flood.

The following cell defines these hydrological, hydraulic and geometric boundary conditions.

# --- the design discharge ----------------------------------------------------
Q_design = 3200.0  # m3/s   Clyde Dam spillway design flow at lake level 195.1 m
                   #        (published; the 500-year, 0.2% AEP flood)

# --- the chute toe and the stilling basin below it ---------------------------
w_chute = 40.0     # m      four 10 m gate bays, idealised as one rectangle
H0 = 50.00         # m      energy head above the un-sunk basin invert (assumed)

# --- the Clutha River below the dam (assumed) --------------------------------
n_manning = 0.045   # s/m^(1/3)  Manning roughness of the downstream reach
slope = 6.0e-4      # -          bed slope of the downstream reach
w_tw = 60.0         # m          width of the downstream reach (rectangular idealisation)
h_tw = 19.060       # m          tailwater depth of that reach in uniform flow

print(f"spillway design flow Q  = {Q_design:7.1f} m3/s")
print(f"chute and basin width w = {w_chute:7.2f} m")
print(f"head at the invert   H0 = {H0:7.2f} m")
spillway design flow Q  =  3200.0 m3/s
chute and basin width w =   40.00 m
head at the invert   H0 =   50.00 m

Grenzberechnung

Einheitsentladung

Für die Berechnung des Wechselsprungs ist eine Entladung pro Meter Breite erforderlich:

q=Qwq = \frac{Q}{w}

The chute delivers this flow supercritically, which is the condition for a jump to form. The critical depth printed below is the upper bound on the entry depth h1h_1, and Part II uses it as the bracket when solving the energy equation.

q_unit = Q_design / w_chute
h_crit = (q_unit**2 / G)**(1 / 3)

print(f"unit discharge   q = Q / w   = {q_unit:7.3f} m2/s")
print(f"critical depth   h_c         = {h_crit:7.3f} m")
print(f"critical velocity            = {q_unit / h_crit:7.3f} m/s")
unit discharge   q = Q / w   =  80.000 m2/s
critical depth   h_c         =   8.673 m
critical velocity            =   9.224 m/s

Wassertiefe htwh_{tw}

Die Tiefe in der stromabwärtigen Reichweite bestimmt, ob der Wechselsprung zurückgehalten oder gefegt wird, und wird durch die Reichweite selbst und nicht durch den Überlauf eingestellt. Für einen rechteckigen Kanal in gleichmäßigem Fluss gibt die Manning-Gleichung

Q=1nMAR2/3S0,tw,A=wtwhtw,R=wtwhtwwtw+2htwQ = \frac{1}{n_M}\,A\,R^{2/3}\,\sqrt{S_{0,tw}}, \qquad A = w_{tw}\,h_{tw}, \qquad R = \frac{w_{tw}\,h_{tw}}{w_{tw} + 2\,h_{tw}}

Evaluating this for the reach above gives htw=19.060h_{tw} = 19.060 m, which is assigned directly in the cell below and used from there on.

Note: Natural channels are not rectangular, and htwh_{tw} enters the retention ratio directly. In practice the tailwater rating curve is obtained from gauging, a numerical model, or terrain data, and a range of tailwater levels is tested rather than a single value.

Die Zelle unten druckt auch die kritische Tiefe des stromabwärts gelegenen Bereichs, da ein Wechselsprung nur im Unterwasser enden kann, während dieser Bereich unterkritisch ist.

h_crit_tw = ((Q_design / w_tw)**2 / G)**(1 / 3)

print(f"tailwater depth h_tw = {h_tw:.3f} m   (given, from the reach above)")
print(f"critical depth of the reach = {h_crit_tw:.3f} m"
      f"   -> {'subcritical' if h_tw > h_crit_tw else 'SUPERCRITICAL'}")
tailwater depth h_tw = 19.060 m   (given, from the reach above)
critical depth of the reach = 6.619 m   -> subcritical

Definieren von Datenstrukturen und Standardwerten

Der folgende Codeblock baut die erforderlichen Datenstrukturen auf und setzt Standardwerte für den Kernteil II.

@dataclass(frozen=True)
class DesignData:
    Q: float       # spillway design flow [m3/s]
    q: float       # discharge per unit width [m2/s]
    H0: float      # energy head above the un-sunk basin invert [m]
    h_tw: float    # tailwater depth [m]
    w: float       # width the basin has to cover [m]


DESIGN = DesignData(
    Q=Q_design,
    q=q_unit,
    H0=H0,
    h_tw=h_tw,
    w=w_chute,
)

print(f"Q      = {DESIGN.Q:8.1f} m3/s   spillway design flow")
print(f"q      = {DESIGN.q:8.3f} m2/s   unit discharge")
print(f"H0     = {DESIGN.H0:8.2f} m      energy head above the un-sunk invert")
print(f"h_tw   = {DESIGN.h_tw:8.3f} m      tailwater depth")
print(f"w      = {DESIGN.w:8.2f} m      width the basin has to cover")
Q      =   3200.0 m3/s   spillway design flow
q      =   80.000 m2/s   unit discharge
H0     =    50.00 m      energy head above the un-sunk invert
h_tw   =   19.060 m      tailwater depth
w      =    40.00 m      width the basin has to cover

Part II: Stilling basin & hydraulic jump design

The sequent depth (Bélanger) equation

For a horizontal, rectangular channel, the position and size of the jump follow from momentum conservation, the hydrostatic pressure forces and continuity. Given that the specific force is equal upstream (1) and downstream (2) of the jump, that is, M1=M2M_1 = M_2 with M=q2/(gh)+h2/2M = q^2/(g\,h) + h^2/2, the depth ratio is calculated by the sequent-depth equation of Bélanger:

  h2h1=12(1+8Fr121)  \boxed{\;\frac{h_2}{h_1} = \frac{1}{2}\left(\sqrt{1 + 8\,Fr_1^{2}} - 1\right)\;}

Notably, h1h_1 and h2h_2 are the sequent (conjugate) depths. Every subsequent quantity in this exercise is obtained from h2h_2: the retention ratio that indicates whether the jump stays in the basin, the basin length, and the required length of downstream scour protection.

Design problem

The position of the jump is not fixed by the spillway. It is controlled by the tailwater depth: a jump forms where the downstream depth matches the conjugate depth h2h_2 belonging to the incoming supercritical state. Where the tailwater is too shallow the jump is swept out onto unprotected downstream riverbed; where it is too deep the jump is drowned and dissipates less.

The single design freedom is the basin depth db\mathbf{d_b}, by which the basin floor is set below the downstream riverbed. Increasing db\mathbf{d_b} acts in two opposing directions:

  1. it increases the energy head H=H0+dbH = H_0 + \mathbf{d_b} above the floor, so the entry flow is faster and shallower, which raises Fr1Fr_1 and hence h2h_2;

  2. it increases the depth available over the floor, namely htw+dbh_{tw} + \mathbf{d_b}.

An acceptable design is a basin depth at which both engineering objectives are satisfied simultaneously:

4.5Fr1<9.0and1.05rt=htw+dbh21.154.5 \le Fr_1 < 9.0 \qquad\text{and}\qquad 1.05 \le r_{\mathrm{t}} = \frac{h_{tw} + \mathbf{d_b}}{h_2} \le 1.15

The first engineering objective is the steady jump that leads to 45% to 70% head loss, and no oscillating surge to fatigue the structure. The second engineering objective requires the basin to hold slightly more water than the jump needs, so that the jump is retained with a small margin without being drowned.

The workflow

The steps run in the order of the table, and each one is either given or one of the three tasks:

contenthint
choose a trial basin depth db\mathbf{d_b}here: 1.0 m (given)
h1h_1 and v1v_1 from the energy equation at the entrancegiven
Fr1=v1/gh1Fr_1 = v_1/\sqrt{g\,h_1}Task 1
is 4.5Fr1<9.04.5 \le Fr_1 < 9.0? if not, adjust db\mathbf{d_b}given
the conjugate depth h2h_2 from the Bélanger equationTask 2
is 1.05rt1.151.05 \le r_{\mathrm{t}} \le 1.15? if not, adjust db\mathbf{d_b}Task 3 + given
basin length lbl_b and scour-protection length lsl_sgiven
head loss ΔH\Delta Hgiven

The three tasks

Each task is one equation from the lecture.

Replace the raise NotImplementedError(...) line with a return statement.

The function names and their arguments must not be changed, because the workflow below calls them.

Important: On completing each task, run the self-check cell. It marks each function [OK] or [XX] against the lecture values.

Vorgestellt: Energiekopf über dem Beckenboden

Neglecting the approach velocity, the energy head available above the basin floor is H=H0+dbH = H_0 + \mathbf{d_b}. At the basin entrance, that is, cross section 1, that head is split between depth and velocity head. With continuity v=q/hv = q/h for a rectangular section,

H=h+v22g=h+q22gh2H = h + \frac{v^2}{2g} = h + \frac{q^2}{2g\,h^2}

Die rechte Seite wird unten in Abhängigkeit von hh und qq codiert. Lesen Sie es, denn der Eintrittszustand jeder Testbeckentiefe kommt daraus: Der angegebene Soldat entry_depth weiter unten wählt die flache, überkritische Wurzel von energy_head(h, q) == H, die der Zweig der Schacht ist.

def energy_head(h, q, g=G):
    '''
    Given: specific energy head of a rectangular section [m].

    Parameters
    ----------
    h : flow depth [m]
    q : discharge per unit width [m2/s]

    Returns
    -------
    the energy head h + q^2 / (2 g h^2) [m]
    '''
    return h + q**2 / (2 * g * h**2)

Aufgabe 1: Froud-Nummer

The Froude number compares the flow velocity with the shallow-water wave speed c=ghc = \sqrt{g h}:

Fr=vghFr = \frac{v}{\sqrt{g\,h}}

Erinnern Sie sich daran, dass Fr>1Fr > 1 überkritische und Fr<1Fr < 1unterkritischer Fluss bedeutet. Dieser Schritt des Workflows berechnet nur den Wert der Froude-Zahl (hier: Fr1Fr_1) für den späteren Vergleich mit dem stationären Fenster:

def froude_number(v, h, g=G):
    '''
    Task 1: Froude number of a rectangular section [-].

    Parameters
    ----------
    v : depth-averaged velocity [m/s]
    h : flow depth [m]
    '''
    # >>> YOUR CODE HERE
    raise NotImplementedError("Task 1: return the Froude number")

Aufgabe 2: Sequenztiefe (Bélanger) Gleichung

** Dies ist die zentrale Gleichung der Übung. ** Implementieren Sie das Tiefenverhältnis an den Querschnitten 2 (h2h_2) und 1 (h1h_1):

h2h1=12(1+8Fr121)\frac{h_2}{h_1} = \frac{1}{2}\left(\sqrt{1 + 8\,Fr_1^{2}} - 1\right)

Note: This equation describes neither the roller between the cross sections nor the internal structure of the jump. Everything the design requires after this point, that is the retention ratio, the basin length and the scour-protection length, follows from the h2h_2 sequent depth equation returns.

def conjugate_depth(h1, Fr1):
    '''
    Task 2: conjugate (sequent) depth downstream of the jump [m].

    Parameters
    ----------
    h1  : supercritical depth upstream of the jump [m]
    Fr1 : Froude number at section 1 [-]
    '''
    # >>> YOUR CODE HERE
    raise NotImplementedError("Task 2: return the conjugate depth h2")

Aufgabe 3: Retentionsverhältnis

Die Wassertiefe über dem Beckenboden ist die Unterwassertiefe plus die Beckentiefe. Vergleicht man es mit der Tiefe, die der Wechselsprung fordert, ergibt sich das Retentionsverhältnis:

rt=htw+dbh2r_{\mathrm{t}} = \frac{h_{tw} + \mathbf{d_b}}{h_2}

rt<1r_{\mathrm{t}} < 1 bedeutet, dass das Becken die Konjugattiefe nicht liefern kann und der Wechselsprung stromabwärts geschwommen wird; rtr_{\mathrm{t}} gut über 1 bedeutet, dass der Wechselsprung ertrunken ist. Der Retentionscheck bittet um 1.05rt1.151.05 \le r_{\mathrm{t}} \le 1.15.

def retention_ratio(h_tw, d_b, h2):
    '''
    Task 3: retention ratio of the basin [-].

    Parameters
    ----------
    h_tw : tailwater depth in the downstream reach [m]
    d_b  : depth of the basin floor below the downstream bed [m]
    h2   : conjugate depth required by the jump [m]
    '''
    # >>> YOUR CODE HERE
    raise NotImplementedError("Task 3: return the retention ratio")

Vorgestellt: Becken- und Geruchsschutzlängen

To empirically derive the required stilling basin length lbl_b, Peterka (USBR Engineering Monograph 25) measured the length of the jump in six test flumes and plotted it against the Froude number as a ready reckoner (his Figure 7, free jump on a horizontal apron). The curve gives a factor (here: flf_l), which is read off at the Froude number of cross section 1 (Fr1Fr_1) and multiplied by the conjugate depth (h2h_2):

| Fr1Fr_1 | 2.4 | 4 | 5 | 6 bis 11 | 14

| flf_{l} | 4.8 | 5.8 | 6.0 | 6.13 | 6.0

Die Funktion peterka_f unten liest diese Tabelle (keine Intervention erforderlich) und gibt flf_{l} zurück. Es passt nichts: np.interp interpoliert linear zwischen den tabellarisierten Punkten einer gemessenen Kurve, und diese Kurve ist keine gerade Linie.

def peterka_f(Fr1):
    '''Given: basin-length multiplier after Peterka (USBR EM 25), interpolated [-].'''
    knots_Fr = [2.4, 4.0, 5.0, 6.0, 11.0, 14.0]
    knots_f = [4.8, 5.8, 6.0, 6.13, 6.13, 6.0]
    return float(np.interp(Fr1, knots_Fr, knots_f))


print(f"f_l at Fr1 = 5.0 : {peterka_f(5.0):.3f}")
print(f"f_l at Fr1 = 8.0 : {peterka_f(8.0):.3f}")
f_l at Fr1 = 5.0 : 6.000
f_l at Fr1 = 8.0 : 6.130

Next, calculate the required basin length lbl_b to contain the jump with the peterka_f function. Because the flow leaving the jump (and the basin end sill) is still turbulent, the riverbed immediately downstream of the basin has to be armoured over a length lsl_s:

lb=fl(Fr1)h2,ls=3.5lbl_b = f_{l}(Fr_1) h_2, \qquad l_s = 3.5 l_b

Beide Längen sind unten codiert, basin_lengths rufen peterka_f für den Multiplikator an.

def basin_lengths(h2, Fr1):
    '''
    Given: basin length and scour-protection length [m].

    Parameters
    ----------
    h2  : conjugate depth downstream of the jump [m]
    Fr1 : Froude number at section 1, which selects the multiplier [-]

    Returns
    -------
    (l_b, l_s) : basin length and scour-protection length [m]
    '''
    l_b = peterka_f(Fr1) * h2
    return l_b, 3.5 * l_b

Hinweis: Für einen stetigen Wechselsprung ist lbl_b in der Nähe der Faustregel ljl_j \approx6 h2h_2, und die Zellen in diesem Notizbuch drucken sowohl ljl_j als auch lbl_b. Andere Designhandbücher würden jedoch unterschiedliche Faktoren angeben, was einer der Gründe ist, warum ein detailliertes Design mit einem physikalischen oder numerischen Modell entscheidend ist.

Selbstkontrolle

Führen Sie diese Zelle nach Abschluss jeder Aufgabe aus. Die Referenzwerte sind die ungefähren Ergebnisse, die in den Vorlesungsschiebern vorgestellt werden, so [OK] auf jeder Zeile angibt, dass die drei Aufgaben die Dias wiedergeben.

CHECKS = [
    ("Task 1  froude_number(31.623, 2.5298)",
     lambda: froude_number(31.623, 2.5298), (6.348,), "-"),
    ("Task 2  conjugate_depth(2.5298, 6.348)",
     lambda: conjugate_depth(2.5298, 6.348), (21.481,), "m"),
    ("Task 3  retention_ratio(19.060, 3.5, 21.481)",
     lambda: retention_ratio(19.060, 3.5, 21.481), (1.050,), "-"),
]


def check_tasks(tolerance=5e-3, verbose=True):
    '''Compare each task against the worked values from the lecture.'''
    passed = 0
    for label, call, expected, unit in CHECKS:
        try:
            value = call()
        except NotImplementedError:
            if verbose:
                print(f"[ ] {label:<46} not implemented yet")
            continue
        got = value if isinstance(value, tuple) else (value,)
        ok = (len(got) == len(expected) and
              all(abs(g - e) <= tolerance * max(1.0, abs(e))
                  for g, e in zip(got, expected)))
        passed += ok
        if verbose:
            mark = "OK" if ok else "XX"
            shown = ", ".join(f"{g:.3f}" for g in got)
            wanted = ", ".join(f"{e:.3f}" for e in expected)
            print(f"[{mark}] {label:<46} {shown:>19} {unit:<3}"
                  f" (expected {wanted})")
    if verbose:
        print("-" * 78)
        print(f"{passed} of {len(CHECKS)} tasks correct.")
    return passed == len(CHECKS)


TASKS_DONE = check_tasks()
[ ] Task 1  froude_number(31.623, 2.5298)          not implemented yet
[ ] Task 2  conjugate_depth(2.5298, 6.348)         not implemented yet
[ ] Task 3  retention_ratio(19.060, 3.5, 21.481)   not implemented yet
------------------------------------------------------------------------------
0 of 3 tasks correct.

Workflow-Implementierung: die Suche über die Beckentiefe

**Der Rest der Berechnungen von Teil II wird angegeben (die Antworten auf die Folgefragen sind nicht). **

Die Funktion basin_state evaluiert das Ende eines Testbeckens und ruft die oben geschriebenen Funktionen an; search_basin_depth wählt die Testtiefen aus, indem Sie db\mathbf{d_b}by-bisection anpassen, bis es die shallowest Tiefe gefunden hat, in der beide Engineering-Ziele erfüllt sind. Die Bisection-Logik sollte vor Ablauf der Zelle gelesen werden.

Fr1Fr_1 and rtr_{\mathrm{t}} increase with db\mathbf{d_b}, which is what allows one to use a single bracket for both tests: too shallow a basin does not supply the depth the jump demands and sweeps it downstream, but too deep a basin supplies more than the jump requires and drowns it. Each failed trial therefore indicates which half of the bracket to retain, and in the present case the search fails in both directions before converging.

** Reservierungen:** Der Such-Workflow beginnt mit einem ersten Test von db\mathbf{d_b} = 1,0 m. Dieser Prozess erfüllt das stetige Stoßfenster, Fr1Fr_1 = 6.1 ist bereits ein stetiger Wechselsprung und versäumt das Rückhaltefenster, der Wechselsprung wird ausgeschwemmt. Die Bissektion vertieft dann das Becken auf 10,5 m, das den Wechselsprung ertrinkt, und arbeitet zurück. Eine akzeptable Tiefe ist nicht das Ende der Suche: Weil ein tieferes Becken Kosten Ausgrabung für keinen Nutzen, hält die Klammer geschlossen, bis die *shallowest akzeptable Tiefe gefunden wird, und dieser Wert wird auf die nächsten 0,25 m für eine konstruktive Figur abgerundet. Das Ergebnis hängt noch von der Breite des Bügels ab, so sollte ein Bericht angeben, welche Klammer es produziert.

FR_WINDOW = (4.5, 9.0)     # steady-jump range
RT_WINDOW = (1.05, 1.15)   # retention window


@dataclass(frozen=True)
class BasinState:
    d_b: float     # trial basin depth [m]
    H: float       # energy head above the basin floor [m]
    h1: float      # supercritical entry depth [m]
    v1: float      # entry velocity [m/s]
    Fr1: float     # entry Froude number [-]
    h2: float      # conjugate depth [m]
    Rt: float      # retention ratio [-]

    @property
    def fr_ok(self):
        return FR_WINDOW[0] <= self.Fr1 < FR_WINDOW[1]

    @property
    def rt_ok(self):
        return RT_WINDOW[0] <= self.Rt <= RT_WINDOW[1]


def critical_depth(q, g=G):
    '''Critical depth of a rectangular section [m]; the bracket for the entry depth.'''
    return (q**2 / g)**(1 / 3)


def entry_depth(H, q):
    '''
    The shallow, supercritical root of energy_head(h, q) = H [m].

    Both roots satisfy the energy equation. The supercritical one lies below the
    critical depth, and it is the branch the spillway delivers, so the bracket is
    closed at the critical depth.
    '''
    return brentq(lambda h: energy_head(h, q) - H, 1e-4, critical_depth(q))


def basin_state(d_b, design=None):
    '''The workflow evaluated for one trial basin depth d_b.'''
    design = design or DESIGN
    H = design.H0 + d_b                          # head above the basin floor
    h1 = entry_depth(H, design.q)                # supercritical root
    v1 = design.q / h1                           # continuity
    Fr1 = froude_number(v1, h1)                  # Task 1
    h2 = conjugate_depth(h1, Fr1)                # Task 2
    Rt = retention_ratio(design.h_tw, d_b, h2)   # Task 3
    return BasinState(d_b=d_b, H=H, h1=h1, v1=v1, Fr1=Fr1, h2=h2, Rt=Rt)
def search_basin_depth(db_start=1.0, db_min=0.0, db_max=20.0, max_iter=25,
                       tol=0.005, grid=0.25, verbose=True):
    '''
    Bisection on the basin depth d_b for the SHALLOWEST depth at which both
    engineering objectives are met, rounded up to the next `grid` metres.

    Returns the accepted BasinState and the full iteration history.
    '''
    d_b = db_start
    history = []
    if verbose:
        print(f"{'iter':>4}{'d_b [m]':>9}{'Fr1':>8}{'h1 [m]':>9}{'h2 [m]':>9}"
              f"{'Rt':>8}   verdict")
        print("-" * 66)

    for i in range(1, max_iter + 1):
        state = basin_state(d_b)
        history.append(state)
        if verbose:
            flags = []
            if not state.fr_ok:
                flags.append("Fr1 low" if state.Fr1 < FR_WINDOW[0] else "Fr1 high")
            if not state.rt_ok:
                flags.append("swept out" if state.Rt < RT_WINDOW[0] else "drowned")
            print(f"{i:>4}{state.d_b:>9.3f}{state.Fr1:>8.2f}{state.h1:>9.4f}"
                  f"{state.h2:>9.4f}{state.Rt:>8.3f}   "
                  f"{'accepted' if not flags else ', '.join(flags)}")

        # A deeper basin raises H, so the entry flow is shallower and faster: Fr1 and Rt increase monotonically with d_b. One bracket therefore serves both criteria, and each verdict says which way to move: a jump that is too gentle or swept out wants a deeper basin, one that is too fierce or drowned wants a shallower one. An acceptable trial is not the end of the search either, because a deeper basin than necessary costs excavation for no benefit, so it too narrows the bracket from above.
        if not state.fr_ok:
            if state.Fr1 < FR_WINDOW[0]:
                db_min = d_b  # jump too gentle: deepen the basin
            else:
                db_max = d_b  # jump too fierce: raise the floor
        elif state.Rt < RT_WINDOW[0]:
            db_min = d_b      # swept out: deeper basin
        else:
            db_max = d_b      # accepted or drowned: try a shallower one

        if db_max - db_min < tol:
            break
        d_b = 0.5 * (db_min + db_max)
    else:
        raise RuntimeError("no acceptable basin depth found in the search range")

    # db_max is the shallowest depth known to work; round it up to a buildable one.
    d_b = math.ceil(db_max / grid) * grid
    state = basin_state(d_b)
    history.append(state)
    if not (state.fr_ok and state.rt_ok):
        raise RuntimeError(f"rounding up to {d_b:.2f} m no longer meets the engineering objectives")
    if verbose:
        print(f"{'->':>4}{state.d_b:>9.3f}{state.Fr1:>8.2f}{state.h1:>9.4f}"
              f"{state.h2:>9.4f}{state.Rt:>8.3f}   shallowest, rounded up")
    return state, history


if TASKS_DONE:
    DESIGN_STATE, HISTORY = search_basin_depth()
    print(f"\naccepted basin depth d_b = {DESIGN_STATE.d_b:.3f} m")
else:
    DESIGN_STATE, HISTORY = None, []
    print("Complete Tasks 1 to 3, then re-run this cell.")
Complete Tasks 1 to 3, then re-run this cell.

Kopfverlust über den Wechselsprung

Der Kopfverlust quantifiziert die Arbeit, die das Becken leistet. Dies ist keine Aufgabe: Die Designentscheidung wurde bereits von den beiden oben genannten Engineering-Zielen getroffen. Der Verlust wird hier berechnet, weil es der Grund ist, warum das Becken existiert. Die Kombination der Energiegleichung mit der konjugierten Tiefenbeziehung auf einem horizontalen Bett ergibt den Kopfverlust in geschlossener Form,

ΔH=H1H2=(h2h1)34h1h2>0\Delta H = H_1 - H_2 = \frac{(h_2 - h_1)^3}{4 h_1 h_2} > 0

ΔH\Delta H ist ein Verlust von Kopf und nicht von Energie: Es stellt die irreversible Umwandlung von mechanischer Mittelflussenergie in Turbulenzen und letztendlich in innere Energie dar, wobei die Gesamtenergie durchweg konserviert wird.

def head_loss(h1, h2):
    '''Given: head loss across the jump [m].'''
    return (h2 - h1)**3 / (4 * h1 * h2)


if TASKS_DONE:
    delta_H = head_loss(DESIGN_STATE.h1, DESIGN_STATE.h2)
    H1 = energy_head(DESIGN_STATE.h1, DESIGN.q)

    print(f"head loss           dH        = {delta_H:8.3f} m")
    print(f"energy head at 1    H1        = {H1:8.3f} m")
    print(f"relative loss       dH / H1   = {delta_H / H1:8.1%}")
else:
    delta_H = H1 = None
    print("Complete Tasks 1 to 3, then re-run this cell.")
Complete Tasks 1 to 3, then re-run this cell.

Länge des Beckens und Scheuerschutz

Die angegebenen basin_lengths, die im angenommenen Design zusammen mit der Daumenregel (ljl_j \approx 6 h2h_2) bewertet wurden, gegen die die Beckenlänge überprüft werden kann.

if TASKS_DONE:
    f_peterka = peterka_f(DESIGN_STATE.Fr1)
    l_b, l_s = basin_lengths(DESIGN_STATE.h2, DESIGN_STATE.Fr1)

    print(f"Peterka multiplier  f_l  = {f_peterka:7.2f}  (at Fr1 = {DESIGN_STATE.Fr1:.2f})")
    print(f"basin length        l_b  = {l_b:7.2f} m   <- given")
    print(f"rule of thumb     6 h_2  = {6 * DESIGN_STATE.h2:7.2f} m"
          f"   ({abs(6 * DESIGN_STATE.h2 / l_b - 1):.1%} from l_b)")
    print(f"scour protection    l_s  = {l_s:7.2f} m   <- given")
else:
    f_peterka = l_b = l_s = None
    print("Complete Tasks 1 to 3, then re-run this cell.")
Complete Tasks 1 to 3, then re-run this cell.

Ergebnisbewertungsflächen

Prüfung der technischen Zielsetzung

Die beiden Engineering-Ziele werden hier grafisch als Funktion der Beckentiefe db\mathbf{d_b} bewertet. Die schattierten Bänder in den Plots sind die Ziele und die gestrichelte vertikale Linie ist das akzeptierte Design. Nur ein Kriterium ist entscheidend: Fr1Fr_1 bleibt in seinem Band über alle Tests hinweg, aber rtr_{\mathrm{t}} tritt in sein Band ein und lässt es innerhalb von etwa 2,5 m Beckentiefe, zwischen 6,79 m und 9,31 m, wieder. Das Retentionskriterium wählt daher db\mathbf{d_b} aus, und es ist das Kriterium, das von der gegebenen Unterwassertiefe htwh_{tw} abhängt.

if TASKS_DONE:
    db_range = np.linspace(0.2, 20.0, 240)
    states = [basin_state(float(x)) for x in db_range]
    Fr_curve = np.array([s.Fr1 for s in states])
    Rt_curve = np.array([s.Rt for s in states])

    fig, axes = plt.subplots(1, 2, figsize=(9.4, 3.6), sharex=True)

    axes[0].axhspan(*FR_WINDOW, color=CYAN, alpha=0.18, lw=0)
    axes[0].plot(db_range, Fr_curve, color=BLUE, lw=2.2)
    axes[0].set_ylabel("$Fr_1$ at the basin entrance [-]")
    axes[0].set_title("Steady-jump window")
    axes[0].set_ylim(4.3, 9.3)
    axes[0].annotate("steady jump\n$4.5 \\leq Fr_1 < 9$", (0.8, 8.4),
                     color=BLUE, fontsize=8.5)

    axes[1].axhspan(Rt_curve.min(), RT_WINDOW[0], color=WARN, alpha=0.10, lw=0)
    axes[1].axhspan(*RT_WINDOW, color=CYAN, alpha=0.18, lw=0)
    axes[1].axhspan(RT_WINDOW[1], Rt_curve.max(), color=GREY, alpha=0.10, lw=0)
    axes[1].axhline(1.0, color=GREY, lw=0.8, ls=":")
    axes[1].plot(db_range, Rt_curve, color=BLUE, lw=2.2)
    axes[1].set_ylabel("retention ratio $r_\\mathrm{t}$ [-]")
    axes[1].set_title("Retention window")
    axes[1].set_ylim(Rt_curve.min(), Rt_curve.max())
    axes[1].annotate("jump swept out", (4.2, 0.83), color=WARN, fontsize=8.5)
    axes[1].annotate("retained", (0.8, 1.09), color=BLUE, fontsize=8.5)
    axes[1].annotate("jump drowned", (0.8, 1.42), color=GREY, fontsize=8.5)

    for ax in axes:
        ax.axvline(DESIGN_STATE.d_b, color=WARN, lw=1.4, ls="--")
        # the design variable is the one symbol set apart from the notation:
        # bold and in the warn colour, on the slides and here alike
        ax.set_xlabel("basin depth $\\mathbf{d_b}$ [m]", color=WARN)
        ax.set_xlim(0.2, 20.0)

    axes[0].plot([DESIGN_STATE.d_b], [DESIGN_STATE.Fr1], "o", color=WARN, ms=6, zorder=3)
    axes[1].plot([DESIGN_STATE.d_b], [DESIGN_STATE.Rt], "o", color=WARN, ms=6, zorder=3)
    axes[0].annotate(f"design\n$\\mathbf{{d_b}} = {DESIGN_STATE.d_b:.2f}$ m,"
                     f"  $Fr_1 = {DESIGN_STATE.Fr1:.2f}$",
                     (DESIGN_STATE.d_b, DESIGN_STATE.Fr1), textcoords="offset points",
                     xytext=(-104, 34), color=WARN, fontsize=8.5,
                     arrowprops=dict(arrowstyle="-", color=WARN, lw=0.8))
    axes[1].annotate(f"$r_\\mathrm{{t}} = {DESIGN_STATE.Rt:.3f}$",
                     (DESIGN_STATE.d_b, DESIGN_STATE.Rt), textcoords="offset points",
                     xytext=(40, -58), color=WARN, fontsize=8.5,
                     arrowprops=dict(arrowstyle="-", color=WARN, lw=0.8))

    fig.tight_layout()
    plt.show()
else:
    print("Complete Tasks 1 to 3, then re-run this cell.")
Complete Tasks 1 to 3, then re-run this cell.

Längsabschnitt des Tosbeckens

Das angenommene Design wird in dem folgenden Codeblock zur Skala gezogen, mit dem nachgeschalteten Flussbett als Datum. Zwei Tiefen sind über dem Tosbeckenboden markiert, und der Unterschied zwischen ihnen ist Gegenstand der Retentionsprüfung:

  • Verfügbar ist die Tiefe, die durch das Versenkwasser und die Tiefe des Beckens bereitgestellt wird, htw+dbh_{tw} + \mathbf{d_b}.

  • Erforderlich ist die für den Wechselsprung erforderliche Tiefe, d.h. die konjugierte Tiefe h2h_2.

Their ratio is rtr_{\mathrm{t}}, and the surplus is the margin by which the jump is retained within the basin rather than on the bed downstream. Only the end depths of the jump follow from the 1d relations, so the surface drawn between cross sections 1 and 2 is indicative.

if TASKS_DONE:
    s = DESIGN_STATE
    floor = -s.d_b                       # basin floor, below the downstream riverbed
    h_avail = DESIGN.h_tw + s.d_b        # depth available over the floor
    h_need = floor + s.h2                # level the jump demands, above the datum
    top = DESIGN.H0                      # energy head above the un-sunk invert
    u = l_b / 24.8                       # one drawing unit, so the layout scales

    x_face, x_toe, x_end = -7.0 * u, 0.0, l_b
    x_tail = x_end + 0.6 * l_b
    x_j0, x_j1 = 0.26 * l_b, 0.62 * l_b

    # every label gets a white glow, so that one crossing a line stays readable
    glow = [pe.withStroke(linewidth=2.6, foreground="white")]

    fig, ax = plt.subplots(figsize=(9.4, 3.4))

    # --- structure and bed ---------------------------------------------------
    # the chute face descends from the spillway crest to the basin floor,
    # then the floor runs to the end sill and the river bed continues downstream
    ax.plot([x_face - 2.0 * u, x_face, x_face + 3.2 * u, x_toe, x_end, x_end, x_tail],
            [top, top, top, floor, floor, 0.0, 0.0],
            color=NAVY, lw=2.4, solid_joinstyle="round")

    # --- water body ----------------------------------------------------------
    xs = np.linspace(x_toe, x_tail, 500)
    bed = np.where(xs <= x_end, floor, 0.0)
    ramp = np.clip((xs - x_j0) / (x_j1 - x_j0), 0.0, 1.0)
    surface = (floor + s.h1) + (DESIGN.h_tw - floor - s.h1) * (
        0.5 - 0.5 * np.cos(math.pi * ramp))
    # a small crest at the end of the jump, so that the roller reads as a roller
    # rather than as a smooth asymptote; it is schematic, like the ramp itself
    surface = surface + 0.04 * (DESIGN.h_tw - floor - s.h1) * np.exp(
        -((xs - x_j1) / (0.09 * l_b))**2)

    ax.fill_between(xs, surface, bed, color=CYAN, alpha=0.30, lw=0)
    ax.plot(xs, surface, color=BLUE, lw=2.0)

    # --- dimensions ----------------------------------------------------------
    def dim(x, y0, y1, label, colour=NAVY, dx=0.7 * u, ha="left", frac=0.5,
            outside=False, ext=0.4 * u):
        '''
        A dimension between two levels, with a tick at each end so that what it
        measures from and to is unambiguous. outside=True puts the two heads
        beyond the span, pointing in, for a span too short to hold them.
        '''
        for y in (y0, y1):
            ax.plot([x - 0.5 * u, x + 0.5 * u], [y, y], color=colour, lw=0.8)
        if outside:
            ax.annotate("", (x, y0), (x, y0 - ext),
                        arrowprops=dict(arrowstyle="->", color=colour, lw=1.1))
            ax.annotate("", (x, y1), (x, y1 + ext),
                        arrowprops=dict(arrowstyle="->", color=colour, lw=1.1))
        else:
            ax.annotate("", (x, y0), (x, y1),
                        arrowprops=dict(arrowstyle="<->", color=colour, lw=1.1))
        if label:
            ax.text(x + dx, y0 + frac * (y1 - y0), label, color=colour,
                    fontsize=8.2, va="center", ha=ha, path_effects=glow)

    # the level the jump demands, carried downstream so that it can be compared
    # with the water surface; it starts right of the jump arrow, never under it
    ax.plot([0.48 * x_end, x_end + 6.0 * u], [h_need] * 2,
            color=WARN, lw=1.0, ls="--")
    dim(0.50 * x_end, floor, h_need,
        f"required\n$h_2 \\approx {s.h2:.1f}$ m", colour=WARN, dx=-0.7 * u,
        ha="right", frac=0.86)
    dim(0.86 * x_end, floor, DESIGN.h_tw,
        f"available\n$h_{{tw}}+\\mathbf{{d_b}} \\approx {h_avail:.1f}$ m",
        dx=-0.7 * u, ha="right")

    # the surplus is 1.1 m on a 22 m bar, so it is named rather than left to the eye
    x_gap = x_end + 4.6 * u
    dim(x_gap, h_need, DESIGN.h_tw, "", colour=WARN, outside=True)
    ax.annotate(f"surplus $\\approx {h_avail - s.h2:.1f}$ m\n"
                f"(water above the level $h_2$ demands)",
                (x_gap, DESIGN.h_tw + 0.6 * u), textcoords="offset points",
                xytext=(0, 32), color=WARN, fontsize=8.2, ha="center",
                arrowprops=dict(arrowstyle="->", color=WARN, lw=0.9),
                path_effects=glow)

    ax.annotate(f"$h_1 \\approx {s.h1:.1f}$ m",
                (x_toe + 3.2 * u, floor + 0.5 * s.h1), textcoords="offset points",
                xytext=(2, 54), color=NAVY, fontsize=8.2,
                arrowprops=dict(arrowstyle="->", color=NAVY, lw=0.9),
                path_effects=glow)
    dim(x_end + 2.4 * u, floor, 0.0,
        f"$\\mathbf{{d_b}} \\approx {s.d_b:.1f}$ m", colour=WARN, outside=True,
        ext=0.8 * u, dx=1.2 * u)
    dim(x_end + 9.0 * u, 0.0, DESIGN.h_tw,
        f"$h_{{tw}} \\approx {DESIGN.h_tw:.1f}$ m")

    ax.annotate("", (x_toe, floor - 0.365 * s.h2), (x_end, floor - 0.365 * s.h2),
                arrowprops=dict(arrowstyle="<->", color=NAVY, lw=1.1))
    ax.text(0.5 * x_end, floor - 0.62 * s.h2,
            f"basin length $l_b \\approx {l_b:.1f}$ m",
            color=NAVY, fontsize=8.2, ha="center", path_effects=glow)

    # --- labels --------------------------------------------------------------
    ax.axhline(0.0, color=GREY, lw=0.7, ls=":")
    # the arrow points at the crest of the roller, and stays above the dashed
    # level line so that it can cross neither that line nor the "required" label
    x_jump = x_j1
    y_jump = float(np.interp(x_jump, xs, surface))
    ax.text(x_jump, y_jump + 1.75 * u, "hydraulic jump", color=NAVY, fontsize=9,
            ha="center", style="italic", path_effects=glow)
    ax.annotate("", (x_jump, y_jump + 0.25 * u), (x_jump, y_jump + 1.45 * u),
                arrowprops=dict(arrowstyle="->", color=NAVY, lw=0.9))
    ax.text(x_face - 1.6 * u, top + 0.12 * s.h2,
            f"from the spillway chute,  $H_0 \\approx {top:.1f}$ m",
            color=NAVY, fontsize=8.2, path_effects=glow)

    ax.set_xlim(x_face - 2.5 * u, x_tail + 1.0 * u)
    ax.set_ylim(floor - 0.75 * s.h2, top + 0.55 * s.h2)
    ax.set_aspect("equal")
    ax.set_xlabel("distance along the basin [m]")
    ax.set_ylabel("level above the\ndownstream bed [m]")
    ax.spines["left"].set_visible(True)
    fig.tight_layout()
    plt.show()
else:
    print("Complete Tasks 1 to 3, then re-run this cell.")
Complete Tasks 1 to 3, then re-run this cell.

Entwurfszusammenfassung

if TASKS_DONE:
    s = DESIGN_STATE
    rows = [
        ("given", "spillway design flow", "Q", DESIGN.Q, "m3/s"),
        ("given", "unit discharge", "q", DESIGN.q, "m2/s"),
        ("given", "energy head above the invert", "H0", DESIGN.H0, "m"),
        ("given", "tailwater depth", "h_tw", DESIGN.h_tw, "m"),
        ("design", "basin depth", "d_b", s.d_b, "m"),
        ("design", "energy head above the floor", "H", s.H, "m"),
        ("design", "entry depth", "h1", s.h1, "m"),
        ("design", "entry velocity", "v1", s.v1, "m/s"),
        ("design", "entry Froude number", "Fr1", s.Fr1, "-"),
        ("design", "conjugate depth", "h2", s.h2, "m"),
        ("design", "retention ratio", "Rt", s.Rt, "-"),
        ("result", "head loss", "dH", delta_H, "m"),
        ("result", "relative head loss", "dH/H1", 100 * delta_H / H1, "%"),
        ("result", "basin length", "l_b", l_b, "m"),
        ("result", "scour protection length", "l_s", l_s, "m"),
    ]

    print(f"{'':8}{'quantity':<34}{'symbol':<14}{'value':>10}  unit")
    group = None
    for kind, name, symbol, value, unit in rows:
        if kind != group:
            print("-" * 70)
            group = kind
        print(f"{kind:<8}{name:<34}{symbol:<14}{value:>10.3f}  {unit}")

    print("=" * 70)
    print(f"windows: Fr1 in [{FR_WINDOW[0]}, {FR_WINDOW[1]}) -> "
          f"{'met' if s.fr_ok else 'NOT met'};  "
          f"Rt in [{RT_WINDOW[0]}, {RT_WINDOW[1]}] -> "
          f"{'met' if s.rt_ok else 'NOT met'}")
else:
    print("Complete Tasks 1 to 3, then re-run this cell.")
Complete Tasks 1 to 3, then re-run this cell.

Follow-up questions

Each of the following requires a single change to one input of the code written above, to explore how uncertainties and changes in the boundary conditions act on the hydraulic jump, and therefore on the stilling basin design.

  1. What happens if the tailwater depth is lower? Recompute with the tailwater depth reduced by 2 m and everything else unchanged, that is, hand basin_state a DesignData whose h_tw is 2 m smaller. Determine the effect on rtr_{\mathrm{t}} and its consequence for the downstream riverbed, and identify how the jump position changes.

  2. How does the jump behave under different discharge scenarios? The basin is designed for a 500-year flood but operates mostly at much lower discharges. So re-evaluate basin_state with a DesignData whose q is halved, and determine whether the jump remains steady and remains retained.

Limits of the simplification

This calculation template uses simplified 1d equations, and its results are therefore subject to considerable uncertainty, related to (but not limited to):

  • hydrology, that is the derivation of the design flood;

  • the tailwater rating curve, instead of the rectangular Manning idealisation;

  • load and failure scenarios, including floods exceeding the spillway design discharge, partial-gate operation, and the sluice gates beside the spillway;

  • cavitation, air entrainment, uplift, fluctuating pressures and fatigue of the structure;

  • scour and riverbed-stability assessment downstream of the protected length;

  • geotechnical analysis and structural design;

  • fish passage and sediment management.

Sources