October 22, :00-16:00. web: math.ubc.ca/ MLRTLM. Math: the art in problem solving. Michael Lindstrom.

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Transcription:

October 22, 2014 15:00-16:00 email: MLRTLM@math.ubc.ca web: math.ubc.ca/ MLRTLM

Math is everywhere quantifiable descriptions glacier motion, spreading of diseases, market inflation, digitally recorded music,... real world model abstractify analyze interpret math is useful

Outline applied math technique intros electrodialysis application fusion application mass spectrometry application concluding remarks

Overview sketch relevant physics, biology, etc. assign variables, write equations insightful results

Example finding the dimensions of a cylindrical tank with open top having a volume of 1000 cm 3 with least possible surface area let h =height, r =radius; need πr 2 h = 1000 with minimum value of 2πrh + πr 2

Example finding the dimensions of a cylindrical tank with open top having a volume of 1000 cm 3 with least possible surface area let h =height, r =radius; need πr 2 h = 1000 with minimum value of 2πrh + πr 2 cheaper than building thousands of cylinders!

Overview make diorama remove dimensions, reduce constants key relationships improved numerics all variables comparable: velocity, pressure, time, etc.

Example rabbit population P has carrying capacity C satisfies P (T ) = rp(1 P/C) at time T, initial population P(0) = P 0 units: [P] = [C] = [P 0 ] = rabbits, [r] = 1/time, [T ] =time nondimensionalize to qualitative behaviour: p 0 p (t) = p(1 p), p(0) = p 0

Overview mathematical impressionism exploit relative smallness of parameter(s) approximate model problem solution accurately solution = estimate + correction + smaller correction +... analytic insight

Example consider 0.0001x 3 x + 1 = 0; let ɛ = 0.0001 1 asymptotic prediction: x 1 + ɛ +... x 1 ɛ 1 2 +... x 1 ɛ 1 2 +... Asymptotic Exact 1.0001... 1.0001... 99.5... 99.496... -100.5... -100.496...

Overview digital snapshot arbitrarily high precision control error terms may require high computational power

Example evaluate I = 1 0 x 5 + 1dx Riemann sum: let N > 0, h = 1/N and x j = jh so that I = h N j=1 x 5 j theory: error + 1 + error some constant N 0 as N N Sum 10 0.999 100 1.066 1000 1.0738 10000 1.0746 100000 1.0747 better methods exist!

Motivation clean water and CO 2 sequestration good many pollutants ionic electrodialysis: filter out impure ions from water, make useful products with electric field and selective membranes

Problem UBC chemical engineers building prototypes, operational conditions important

Problem UBC chemical engineers building prototypes, operational conditions important Given experimental data of input concentrations, the total voltage and the total current drawn across the series of channels, what losses can be attributed to each individual channel and what is taking place in each channel?

Carbonic Acid Channel given voltage drop V, determine the current I

Models model 0: uniform [H + ] and [HCO 3 ], current driven by voltage gradient - wrong species cross membranes

Models model 0: uniform [H + ] and [HCO 3 ], current driven by voltage gradient - wrong species cross membranes model 1: spatially varying [H + ] and [HCO 3 ] without reactions - too few ions

Models model 0: uniform [H + ] and [HCO 3 ], current driven by voltage gradient - wrong species cross membranes model 1: spatially varying [H + ] and [HCO 3 ] without reactions - too few ions model 2: with reactions but ions not produced fast enough #fail

Models model 3

Models numerics on asymptotic model more consistent with experimental data discovered device doesn t operate the way intended!

Models numerics on asymptotic model more consistent with experimental data discovered device doesn t operate the way intended!... all models are wrong, but some are useful. - George Box

Motivation fusion energy in sun 3 1 H + 2 1 H 4 2 He + 1 0 n + 17.6 MeV and other reactions clean energy sustain high particle density and temperature fusion on earth? magnetized target fusion at General design: compress plasma in imploding shell of lead-lithium, driven by fast high-pressure impulses

Problem

Problem How much will the plasma compress under such a design?

Simple Dimensionless Model spherical symmetry homogeneous plasma nonlinear, coupled system of PDEs: mass and momentum conservation free boundaries - need to solve for radii with nondimensionalization small initial plasma radius very small initial density disturbance very small impulse time very, very small initial plasma pressure

Insights Obtained wave-like behaviour: sound speed dominates pressure amplitude grows like 1/r almost all input energy reflected! fusion may be within reach - Lawson condition

Insights Obtained minimum radius R L : R L C 4 s P plasma,0 R 7 inner,0 ϱ3 0 πp 4 maxr 4 outer,0 T 2 0 agrees well with numerical methods Parameter C s P plasma,0 R inner,0 ϱ 0 P max R outer,0 T 0 = 4mm Meaning lead sound speed at atmospheric pressure initial plasma pressure initial plasma radius lead density at atmospheric pressure piston impulse pressure initial lead radius impulse time scale

Spectrometry Motivation and Problem detect chemical species/isotopes with mass charge-to-mass separation in mass spectrometer some current means magnetic fields costly time of flight discrete quadrupole too specific

Spectrometry Motivation and Problem detect chemical species/isotopes with mass charge-to-mass separation in mass spectrometer some current means magnetic fields costly time of flight discrete quadrupole too specific PerkinElmer: come up with a design for a mass-spectrometer without magnetic fields, with continuous measurement and which can detect any mass.

Concepts acceleration in electric field proportional to charge-to-mass ratio and field strength positive charge oscillates between fixed positive charges (one-dimensional) same amplitude and different masses, different periods

Idea fire ion beam into tube of charges predict qualitative trajectories via asymptotics oscillation wavelength mass-dependent numerics of ODEs verify distinct masses spatially separate

Results

Art each technique has role combination often useful results extremely beautiful/satisfying

Final Remarks thanks to many collaborators on these projects: - Arman Bonakdarpour, Saad Dara, and David Wilkinson (UBC Chemical and Biological Engineering Department) - Sandra Barsky and Aaron Froese (General ) - Iain Moyles, Ward, and Brian Wetton (UBC Math Department) - Samad Bazargan (PerkinElmer) - others some suggested applied courses: - MATH 215, 316, 400, 401 (differential equations) - MATH 361 (modelling, math-bio) - MATH 210, 405 (numerics) - MATH 450 (asymptotics) - some non-math science courses! slides posted at: math.ubc.ca/ MLRTLM/#talks