G. Groot Gregory

Automated control of manufacturing sensitivity during optimization

Immediately following an optimization sequence, many designers typically implement sensitivity analysis prior to more intensive tolerance analysis and system error budgeting. This paper proposes a method of automating optical design optimization into a two stage process which incorporates design sensitivity into the optimization process. The first stage consists of the standard optimization approach where the error function is a user defined combination of system performance as well as optical and physical parameter constraints. The second stage amends the error function to include the minimization of incident ray angles on each optical surface as part of the error function. The amendment to the error function in the second stage targets the root mean square of incident angles of sample rays. These rays may typically consist of the marginal ray to the image center, as well as the upper and lower rim rays to the image corner. A priority is placed on reducing large angles as the result of a least squares method. This paper will address the detailed implementation of the proposed approach inside of the optical design program. Practical examples will be presented where the proposed optimization has reduced the system sensitivity to manufacturing errors without substantially effecting image quality. The results of incorporating the amended error function into an automated global optimization approach will be described.

Using Spline Surfaces in Optical Design Software

Splines are commonly used to describe smooth freeform surfaces in Computer Aided Design (CAD) and computer graphic rendering programs. Various spline surface implementations are also available in optical design programs including lens design software. These surface forms may be used to describe general aspheric surfaces, surfaces thermally perturbed and interpolated surfaces from data sets. Splines are often used to fit a surface to a set of data points either on the surface or acting as control points. Spline functions are piecewise cubic polynomials defined over several discrete intervals. Continuity conditions are assigned at the intersections as the function crosses intervals defining a smooth transition. Bi-Cubic splines provide C2 continuity, meaning that the first and second derivatives are equal at the crossover point. C2 continuity is useful outcome of this interpolation for optical surface representation. This analysis will provide a review of the various types of spline interpolation methods used and consider additional forms that may be useful. A summary of the data inputs necessary for two and three-dimensional splines will be included. An assessment will be made for the fitting accuracy of the various types of splines to optical surfaces. And a survey of applications of spline surfaces in optical systems analysis will be presented.

Modeling the operating conditions of solar concentrator systems

Converting energy from the suns radiation into electrical current has been a reality for over 40 years but the efficiency derived from these devices has been low and not economically practical. With recent developments in solar cell technology, including multi-junction cells, conversion efficiency of nearly 40% has been demonstrated in the laboratory. The efficiency gain is due to the structure of the cell coupled with optics used to concentrate the sunlight onto the device. The concentrator design requires that the cell be uniformly illuminated to achieve the highest efficiency. Optical analysis software is used in the design and simulation of the system comprised of the solar radiation, optical concentrator and solar cell. This paper will describe the modeling of these concentrators and illustrate how the simulation can provide improved designs to achieve high illumination uniformity.

Statistical variation of color uniformity for solid-state illumination systems

Color uniformity is an important performance metric for many solid-state lighting systems, particularly those systems that use multiple light-emitting diodes (LEDs) to produce the desired illumination distribution. Once the optical design is done, however, it is important to understand how the color uniformity changes when LEDs from within a single color-bin are mixed. Can the design tolerate any LED within the color-bin? Are the inter-bin color variations noticeable in the beam distribution? Are they noticeable when looking back at the luminaire? This paper looks at this question using an exterior automotive stop lamp. The statistical variation of color uniformity is analyzed using assumed interbin statistical variation for the color of the LEDs.

Front Matter: Volume 8481

This PDF file contains the front matter associated with SPIE Proceedings Volume 8481 including the Title Page, Copyright information, Table of Contents, Introduction (if any), and the Conference Committee listing.

Front Matter: Volume 7783

This PDF file contains the front matter associated with SPIE Proceedings Volume 7783, including the Title Page, Copyright information, Table of Contents, Introduction, and the Conference Committee listing.© (2010) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Front Matter: Volume 6668

This PDF file contains the front matter associated with SPIE Proceedings Volume 6668, including the Title Page, Copyright information, Table of Contents, Introduction (if any), and the Conference Committee listing.

Multiple methods of modeling MEMS

Micro-Electro-Mechanical Systems or MEMS are becoming increasingly important in several optical applications. In particular, devices composed of an array of active micro-optics can be used for wavefront correction, optical switching, and generic digital light control. Whatever the application, it is important for anyone seeking to employ this technology to use computer modeling to predict the performance of the subsystem that incorporates optical MEMS. In this paper we will show how commercially available software can be used to model these systems using several approaches.

Modeling aspheric tolerances in lens design software I

Sources of error associated with Single Point Diamond Turning of rotationally symmetric aspheres are examined and mathematically dissected to yield equations in the form of a superposition of errors. The equations are derived from manufacturing process considerations involving CNC machining mechanics or operator observations. The types of errors reviewed here include geometry errors, displacement errors, and dynamic errors but do not include errors associated with thermal gradients.

Using software interoperability to achieve a virtual design environment

A variety of simulation tools, including optical design and analysis, have benefited by many years of evolution in software functionality and computing power, thus making the notion of virtual design environments a reality. To simulate the optical characteristics of a system, one needs to include optical performance, mechanical design and manufacturing aspects simultaneously. To date, no single software program offers a universal solution. One approach to achieve an integrated environment is to select tools that offer a high degree of interoperability. This allows the selection of the best tools for each aspect of the design working in concert to solve the problem. This paper discusses the issues of how to assemble a design environment and provides an example of a combination of tools for illumination design. We begin by offering a broad definition of interoperability from an optical analysis perspective. This definition includes aspects of file interchange formats, software communications protocols and customized applications. One example solution is proposed by combining SolidWorks1 for computer-aided design (CAD), TracePro2 for optical analysis and MATLAB3 as the mathematical engine for tolerance analysis. The resulting virtual tool will be applied to a lightpipe design task to illustrate how such a system can be used.