Chapter Review · a rapid pre-test review (speedrun)

Geometric Modeling and Design: Chapter Review

A rapid review before the test: the chapter's vocabulary and notation, every formula with the conditions to use it, the standard problem types step by step, and the traps that cost points.

Vocabulary and notation

Geometric model and simplifying assumption
A geometric model represents an object or space with familiar shapes to answer a particular question. A simplifying assumption leaves out or idealizes a detail for that purpose.
Measured and stipulated inputs
A measured dimension comes from a reading. A stipulated dimension is fixed for the calculation.
Measurement interval
The range of unrounded readings that can produce a report under the stated rounding rule.
Prediction interval from these inputs
The range of model outputs allowed by the stated input bounds and assumptions. It carries no probability or confidence level.
Independent observation
A check of the target quantity using separate evidence, such as a grid survey of an area predicted from tape readings.
Area density and mass density
Area density describes a quantity per unit of area, such as residents per square kilometer. Mass density describes mass per unit of volume.
Uniform model and homogeneous material
A uniform model uses the same density throughout the region or material. A homogeneous material has uniform composition and density under the modeled conditions.
Scale and capacity
A scale matches corresponding model and actual lengths. Capacity is available volume inside a container up to the stated limit.
Constraint, feasible design, and objective
A constraint is a requirement. A feasible design meets every requirement. The objective is the quantity to maximize or minimize among feasible designs.
Layout family
The set of layouts that obey specified placement rules, such as one layer and one orientation per row.
Best tested and proven optimum
Best tested means best among the feasible designs compared. A proven optimum is achieved by a feasible design and no design allowed by the model improves on it.

Formulas and theorems

  • Readings behind a rounded report

    r−Δ2≤x<r+Δ2r-\tfrac{\Delta}{2}\le x<r+\tfrac{\Delta}{2}
    Readings that round to 8.6 centimetersOn a number line, the segment starts at a filled point at 8.55 centimeters, passes through the reported value of 8.6 centimeters, and stops at a hollow point at 8.65 centimeters.IncludedExcluded8.558.68.65Reading (cm)
    Text description

    The included segment starts at a filled point at 8.55 centimeters. The report of 8.6 centimeters lies in the middle. A hollow point at 8.65 centimeters excludes that reading. The lower halfway reading rounds up to 8.6 and the upper halfway reading rounds up to 8.7.

    Use when A positive reading xx is reported as rr to the nearest step Δ\Delta, with ties going to the larger report. Keep any physical limits on xx. The rounding rule bounds the original reading. Instrument or placement error needs separate information.

    e.g. A positive length is reported as 8.6 cm to the nearest tenth, with ties rounded up. Find the possible readings in centimeters. They satisfy 8.55≤x<8.658.55\le x<8.65.

  • Area after a rectangular cutout

    A=Lw−bvA=Lw-bv
    Separate widths and a shared widthThe first panel shows a cutout strictly inside a rectangle. The outer width is w and the cutout width is v. The second panel shows a strip removed across the full width, so both the whole and the strip use w.Interior cutoutFull-width cutoutwholevwstripw
    Text description

    Two schematic top views compare a cutout that fits inside a rectangle with a cutout that spans the full width. The interior hole has its own width v, measured in the same direction as the outer width w. The second cutout is an end strip that runs from the top to the bottom edge, so it has the same width w as the whole rectangle.

    Use when The cutout of length bb and width vv fits inside the rectangle of length LL and width ww. With positive fixed lengths, larger ww raises AA at fixed vv, and larger vv lowers AA at fixed ww. For a full-width strip, set v=wv=w before bounding.

    e.g. Outer and cutout lengths are 9.5 m and 2.5 m. Their independent widths range from 3.2 to 3.4 m and 0.9 to 1.1 m, respectively, excluding each upper endpoint. The cutout always fits. Find the remaining area range in square meters. It is 27.65<A<30.0527.65<A<30.05.

  • Area density and combined regions

    d=NAN=dAA=Nddcombined=N1+N2A1+A2\begin{gathered} d=\frac{N}{A}\\ N=dA\\ A=\frac{N}{d}\\ d_{\text{combined}}=\frac{N_1+N_2}{A_1+A_2} \end{gathered}

    Use when NN is the count or total quantity for the same region as its positive area AA. Divide by dd only if positive. Transfer a rate to another region only if it represents that region. Combine nonoverlapping regions by adding totals, or subtract a known part's count and area to find the remainder.

  • Mass, volume, and density

    ρ=mVm=ρVV=mρ\begin{gathered} \rho=\frac{m}{V}\\ m=\rho V\\ V=\frac{m}{\rho} \end{gathered}

    Use when Use positive volume VV and the density for that volume. Divide by ρ\rho only if positive. A material density applies to the occupied material volume. The average density of a hollow object using its outer volume divides by the whole volume, including the cavity.

  • Model-to-actual length, area, and volume

    k=LactualLmodelLactual=kLmodelAactual=k2AmodelVactual=k3Vmodel\begin{gathered} k=\frac{L_{\text{actual}}}{L_{\text{model}}}\\ L_{\text{actual}}=kL_{\text{model}}\\ A_{\text{actual}}=k^2A_{\text{model}}\\ V_{\text{actual}}=k^3V_{\text{model}} \end{gathered}

    Use when A ratio 1:k1:k puts model first in common units. For area or volume, the same positive length factor must apply in every measured direction. Reverse by dividing by the same power. To recover kk from a matching area or volume ratio, take its positive square or cube root. Square or cube the units too if using a conversion such as meters per map centimeter.

  • Rectangular capacity and volume units

    Vfill=Ainside basehfill1 L=1000 cm3\begin{gathered} V_{\text{fill}}=A_{\text{inside base}}h_{\text{fill}}\\ 1\text{ L}=1000\text{ cm}^3 \end{gathered}

    Use when Use the inside base and depth from the floor to the fill line or rim. The fill fraction equals the depth fraction when horizontal cross-sectional area is constant. Apply cubic scaling to capacity only for similar interiors at corresponding fill levels.

  • Fencing cost and planted area

    C=2rss+2rddA=sd\begin{gathered} C=2r_s s+2r_d d\\ A=sd \end{gathered}

    Use when For a rectangle, both parallel sides of length ss cost rate rsr_s per unit length, and both perpendicular sides of length dd cost rdr_d. Recount only the lengths bought if an edge is supplied. Price gates separately. Use the full rectangle area when all of it is plantable.

  • Box faces, purchased board, and cost

    S=2(ℓw+ℓh+wh)B=Sneeded+WC=rB+F\begin{gathered} S=2(\ell w+\ell h+wh)\\ B=S_{\text{needed}}+W\\ C=rB+F \end{gathered}

    Use when SS counts six faces of a closed rectangular box with face dimensions ℓ,w,h\ell,w,h. Add material for any divider or overlap to get SneededS_{\text{needed}}, and add waste area WW. With a positive area rate rr and fixed fee FF, charge for purchased area BB. If sold in whole sheets, price the sheets bought and verify the cutting layout fits.

  • Items in one row

    na+(n−1)g≤Lna+(n-1)g\le L

    Use when For n≥1n\ge1 whole items of width a>0a>0 along a usable row of length LL, use the minimum gap g≥0g\ge0 between neighbors and no required end gaps. With no gaps, round L/aL/a down. If one item cannot fit, the maximum is zero.

  • Minimum sum at fixed product

    (a+b)2=4ab+(a−b)2a+b≥2ab\begin{gathered} (a+b)^2=4ab+(a-b)^2\\ a+b\ge 2\sqrt{ab} \end{gathered}

    Use when For positive a,ba,b of fixed product, equality requires a=ba=b. If the variable material terms are 3w3w and 2ℓ2\ell, balance those terms. Verify that the resulting dimensions satisfy every constraint.

  • Maximum product at fixed sum

    x+y=Txy=(T2)2−(x−T2)2\begin{gathered} x+y=T\\ xy=\left(\tfrac T2\right)^2-\left(x-\tfrac T2\right)^2 \end{gathered}

    Use when For positive x,yx,y with fixed sum TT, the product reaches its upper bound at x=y=T/2x=y=T/2 if that pair is feasible. With a cap x+y≤Tx+y\le T, the bound still holds, and attaining it requires both the full sum and equal terms.

Problem types, step by step

Choose shapes and check the size of a calculation

  1. Name the quantity and choose shapes that capture it. Add pieces with disjoint interiors and subtract holes. For a triangle or trapezoid use perpendicular height.
  2. Separate recorded measurements from values fixed by the model. State any omitted detail that could change the result.
  3. Convert lengths to common units and estimate with nearby easy numbers. Compare the calculation with the estimate and report units appropriate to the quantity.

Bound a prediction with uncertain dimensions

  1. Write each allowed input range and mark which endpoints are included. Use one variable for each shared measurement before simplifying.
  2. Check the direction of change throughout the allowed range. For a larger input that raises the result, use its low end for the lower bound. If a larger input lowers the result, use its high end instead.
  3. Check that the proposed endpoint combination is allowed or can be approached by allowed combinations. In strictly increasing or decreasing cases, an excluded input endpoint makes the corresponding output bound unattained.

e.g. A rectangular deck is 14 m long. A 3.5 m long end strip is removed across its full width. The width can be at least 2.4 m and less than 2.8 m. Find the remaining area range in square meters. It is 25.2≤A<29.425.2\le A<29.4.

Check and revise a model with separate data

  1. Compare an independent observation of the same quantity with the prediction. Check endpoint inclusion. If both estimates are intervals, check whether they share any allowed values.
  2. Agreement supports that prediction under its assumptions. Disagreement gives a reason to check the inputs, the shape assumptions, and the separate observation.
  3. Use field evidence to add a missed patch or remove an extra patch. For a fixed correction, shift both bounds without changing inclusion. Test a revision with fresh evidence.

e.g. A ramp model predicts 3636 to 38 m238\text{ m}^2, inclusive. A separate survey gives 39 m239\text{ m}^2. A missed nonoverlapping patch adds a fixed 2.5 m22.5\text{ m}^2. Find the revised range and compare. The range is 38.538.5 to 40.5 m240.5\text{ m}^2, inclusive, so the survey agrees.

Combine and interpret area densities

  1. Find the count for each actual region, using its applicable rate if needed. Convert areas to the same unit.
  2. For disjoint regions, divide the total count by the total area. To solve for an unknown part, use that the individual counts add to the total, and the individual areas add to the whole area.

Use scale and density in one prediction

  1. Find the scale direction from corresponding lengths. Convert the horizontal dimensions of a plan before multiplying by a separately given actual depth.
  2. Use the inside volume to the relevant fill level for capacity, or subtract cavities to find material volume. Convert the area or volume to the density's denominator unit.
  3. Multiply by the applicable actual density to find a count or mass. For a fit or load limit, divide the allowed mass by its positive density and compare with available volume. Check the size against a familiar amount.
  4. For similar solids of the same homogeneous material under the same conditions, mass scales with volume and density stays fixed. For a resized drawing representing the same count, divide the count by the new paper area.

e.g. A tank model holds 175 cm3175\text{ cm}^3 up to its fill line. The actual interior and line correspond at scale 1:61:6. Find the mass at that line for a liquid of density 1.1 kg/L1.1\text{ kg/L}. The capacity there is 37.8 L37.8\text{ L} and the mass is 41.58 kg41.58\text{ kg}.

Compare feasible designs before and after a change

  1. Write all limits and the objective. Evaluate area, capacity, material or cost as required. Check orientation, allowable dimensions, and whether equality is allowed at each cap or minimum.
  2. Filter the proposals before ranking them on the stated objective. Equal objective values tie unless the problem gives a further rule.
  3. If a site, cost, waste, or clearance assumption changes, redo the affected checks and compare the surviving designs. Use cost per piece when that is the objective.

Certify a packing count

  1. State the allowed orientations, usable dimensions, and clearances. For a uniform grid, test each allowed orientation by counting whole items across and whole rows deep.
  2. If full-width rows may differ in orientation, find each orientation's count across. List every possible count of deeper rows. For each case, fill the remaining depth with as many shallower rows as fit.
  3. Give a placement reaching the largest count. For any single-layer, nonoverlapping packing, container area divided by item area, rounded down, is an upper bound. It proves the wider maximum if an allowed layout reaches it.

e.g. Pack 9-by-4 cm tiles in a 26-by-22 cm tray in one layer of full-width rows, edges aligned, one orientation per row, with touching allowed. Find the most tiles. Two 9 cm deep rows and one 4 cm deep row achieve the row-family maximum of 14.

Prove an optimum over the feasible domain

  1. Describe every allowed choice, including whether dimensions are whole numbers or positive real numbers. Use a constraint to relate dimensions when possible.
  2. For a finite set, cover all choices or justify ruling out the rest. One better feasible design can refute a proposed optimum.
  3. For varying dimensions, prove a bound for the objective over the entire feasible domain. A fixed product can bound a sum below. A fixed sum can bound a product above.
  4. Check that a feasible design attains the bound. If the equality case is excluded, the bound alone does not identify the optimum.

e.g. A rectangle may have any positive side lengths with a total perimeter of 52 m. Find the greatest area. It is 169 m2169\text{ m}^2, attained by the 13 m square.

Find when a recommendation changes

  1. Write each feasible design's objective as a function of the changed input, such as the board waste, price per meter, or width of a clear strip.
  2. If the two linear expressions cross, set them equal to find the tie and check which design wins on each allowed side. For a whole-item packing, recheck the counts at the new dimensions.

e.g. Two feasible packages cost 87 and 96 cents. Only the cheaper design gains waste, charged at 0.6 cents per square centimeter. Find the waste area that makes them tie. It is 15 cm215\text{ cm}^2.

Exam traps

  • Trap Moving all uncertain inputs in the same direction

    Fix A bigger hole removes more material. Use opposite ends for whole and removed terms only if the needed choices can coexist. Keep a shared dimension at one value.

  • Trap Calling an excluded bound a maximum or minimum

    Fix A bound may be approached without being attained. When a prediction decreases as its input rises, the input's high end gives the output's low end.

  • Trap Treating precise arithmetic as evidence about the actual shape

    Fix Rounding bounds cover only the uncertainty modeled. An estimate made from the same inputs checks the size of the calculation. Use separate evidence to check the real target.

  • Trap Cubing a scale from a top view or from a container's exterior

    Fix A top view supplies two directions. Use a separate depth when needed. Capacity requires the interior and the stated fill level.

  • Trap Calling a sampled winner a proven optimum

    Fix State the design set actually covered. An exhaustive comparison or an attained bound proves optimality for that set.

Chapter Test Questions from across the chapter