灯峰阁设计lightools v7软件视频教程软件教程lighttools2013年extractor pattern design for3d textured displays and light pipes

1、Extractor Pattern Design for 3D Textured Displays and Light PipesDr. William J. CassarlyOptical Research Associates Abstract:The design of backlit displays and light guides used in instrument lighting often includes the use of 3D textures on the flat surfaces of a complicated plastic part. This talk

2、 will describe an iterative technique that can automatically define the texture pattern for a desired spatial luminance distribution by using illumination simulation results. Numerous examples using LEDs and CCFLs will be demonstrated. OutlineDisplay devicesBacklightsInstrument PanelsAppliquOptimiza

3、tion Elements of an optimizerMerit Function and NoiseMesh Feedback OptimizationExamplesVariable size and placement 1D (CCFL) and 2D (LED) SummaryWhat Is A Backlight?BacklightsLCD backlightInstrument PanelsAppliqusetcNominally Consists ofA light guideUsually made of plasticA light sourceCCFL and LED

4、are typicalOptic to increase collection efficiencyOther elements often usedDiffuser Brightness enhancing filmsBackplane reflectorSome elements may not be used, depending on size, cost, and other requirementsTypical BacklightLight sourceLight guideDiffuser + BEFReflectorReflectorTypical Design GoalEx

5、tract light in a direction perpendicular to the direction of propagationSpatial light modulator (e.g., LCD or Appliqu) is placed over the backlightTypically want uniform light extractionLight SourcePreferred direction of light extractionDirection of light propagationLight GuideLight extraction from

6、a light guideDesign Process: UniformityAvailable power varies within the light guideExtraction efficiency varies along length to compensate Ways to vary extraction efficiency include Paint density, Texture size, Texture spacingNeed a means to design the extraction patternDistance from the sourceAvai

7、lable powerExtraction efficiencyUniform outputOptimizationOptimizationAbility to automatically refine the performance of a system based upon a user specified performance criteriaParameterizationDefinition of system variablesChoose variables that influence performanceMerit FunctionQuantifies system p

8、erformanceSmaller value means better performanceAlgorithmVarious possible methodsLocal versus globalOptimization AlgorithmMerit FunctionModelParameterizationUser Interface ties these elements togetherOptimization FlowchartEvaluate Merit FunctionCompare MF With Termination CriteriaSetupAlgorithm Comp

9、utes New Variable ValuesUpdate ModelDoneMerit FunctionOptimizer needs quantity to determine goodnessCalled the Merit Function, MFWeighted Sum of the Squares is typicalSmallest MF when Vi = Ti for all iWeights, Wi, control relative importance of the Vi - TiMF = Wi2(Vi - Ti)2Wi = Weight of ith MF item

10、 Vi = Current Value of ith MF itemTi = Target of ith MF itemTerminationVi can be obtained using Monte Carlo simulationsValues have noise, i, and therefore the Merit Function has noiseLightTools computes the noise in the Merit FunctionTypically, reduce noise by tracing more raysOptimizer terminates w

11、hen Noise es large relative to MFLuminance with10,000 RaysLuminancewith1,000,000 RaysMF = Wi2(Vi + i - Ti)2MF = Wi2(Vi - Ti)2 + NoiseFeedback OptimizationMost backlights represent a very special type of illumination systemThere is a 1:1 correlation between the extractor position and the spatial lumi

12、nance distributionProperties of paint or 3D texture extractor elements (size, depth, position, etc.) affect the luminance distribution in a relatively localized manner An efficient optimization algorithm is possible because of this correlation This approach is very powerful and will be described ove

13、r the next few slidesMesh Feedback OptimizationUniformity obtained by iteratively changing the paint or texture pattern Reduce extraction where (il)luminance is too highIncrease extraction where (il)luminance is too lowAmazingly robustSTARTING PATTERN CAN BE FAR FROM FINAL PATTERNEvaluate (il)Lumina

14、nceAdjust Extraction PatternUniformity OK?NOYESExamplesChanging Size3D texture placement does not change, but extraction efficiency depends upon feature sizePaint density (size of paint dot)Prism Width/DepthSphere or Cone Tip DepthChanging PlacementFeature size stays constant, but extraction efficie

15、ncy depends upon relative spacingTypically chosen to avoid step of painting the backlight by integrating placement features into the moldExample 1, CCFL with Painted LP6 merit function evaluations to obtain reasonable solution for 2D texture pattern with uniform grid at startSmall Source(e.g., LED)2

16、D DisplayTexture PatternOutputExample 2, LED with Painted LPSingle 120 LED, air space between LED and light pipeMax density near the input (left) edgeStartFinalExample 3, LED with Painted LP and CutoutSingle LED with circular cutout near the inputMax density near the far (right) edgeCircular cutoutS

17、tartFinalExample 4: Prism Width ExampleLambertian LED located along left edge of backlightSurface composed of +/-45 prisms with the width variable. Prisms are rotated 45 with respect to the backlight edges.Resulting prism width distribution is very non-uniform, but output is uniformPrism Width Distr

18、ibution StartFinalTexture PatternOutputExample 5: Sphere DepthLambertian LED located along left edge of back lightSurface composed of equally spaced spheres with constant radiusNo paint applied to the textureSurface to vertex of sphere is variedSurface to VertexSurface to Vertex DistributionFinal Lu

19、minanceExample 6, Paint Density with NonUniform TargetThis example illustrates a target distribution that is not constant. The letters L and T have target values that are twice the background.Texture PatternOutputStartFinal3D Textures, PlacementChanging 3D texture spacing is more complicated than ch

20、anging feature size Typically need to avoid overlap of 3D texturesSpacing changes in one region can alter spacing in another Total number of 3D textures can change2D extraction pattern is more complicated than 1DPrism Spacing with CCFLPolynomial prism spacing coefficients controlledPrism Spacing, Af

21、terPrism Spacing, BeforeOptimize with 5000 ray, Results shown below with 50,000 raysSpecify 2D DensityZone is divided into Nx by Ny binsArea = BinAreaBins contain 3D textures Number = Nij3D textures fit inside rectanglesRectangle Area = ADensityij = Nij(A/BinArea)2D Placement2D spacing is defined us

22、ing 2D mesh. Within each bin of the mesh, spacing is either uniform in X and Y, or neighboring bins are used to compute a slope term and the spacing is varied linearly across a bin.Number of bins equals number of mesh bins, by default, but user can over-ride2X24X44X4 with linear changeDither Within

23、a BinDither allows textures to have random shifts with respect to their nominal centers, but randomization is controlled so that textures do not overlapDither X,Y=1,0Dither X,Y=0,1Dither X,Y=1,1Dither X,Y=0,0Dither X,Y=.2,.2Dither X,Y=.5,.5Placement with Hemisphere TexturesNonuniform placement of id

24、entical textures is used to vary the extraction efficiencyThis example uses smooth hemisphere textures (i.e., no diffuse paint on the textures)Texture DensityOutputLEDStartFinalTwo LEDs, No SymmetryPlacement exampleTwo LEDs No symmetryLEDsStartFinalTexture DensityOutputTexture DensityOutputTwo LEDs,

25、 Some SymmetryPlacement exampleTwo LEDsSome symmetryTexture DensityOutputLEDsStartFinalTexture DensityOutputZero Target Edge BinsIt is not always desired to have the edge region of the light pipe lit By using zero targets around the edge, uniform output within the center region is obtainedNotice tha

26、t optimization increases density near edges of the targetTexture DensityOutputLEDZero target edge binsTexture DensityOutputStartFinalNonrectangular Shape ExampleA new feature in LT computes area of partial bins areas on a surfaceThis example uses the partial areas as the optimization targetsTexture DensityOutputLEDCutoutsMatching Targetpartial edge binsTexture DensityOutputStartFinalPrismatic FilmsPrismatic films are often add