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NASA NTRS1996

CometBoards Users Manual Release 1.0

Several nonlinear mathematical programming algorithms for structural design applications are available at present. These include the sequence of unconstrained minimizations technique, the method of feasible directions, and the sequential quadratic programming technique. The optimality criteria technique and the fully utilized design concept are two other structural design methods. A project was undertaken to bring all these design methods under a common computer environment so that a designer can select any one of these tools that may be suitable for his/her application. To facilitate selection of a design algorithm, to validate and check out the computer code, and to ascertain the relative merits of the design tools, modest finite element structural analysis programs based on the concept of stiffness and integrated force methods have been coupled to each design method. The code that contains both these design and analysis tools, by reading input information from analysis and design data files, can cast the design of a structure as a minimum-weight optimization problem. The code can then solve it with a user-specified optimization technique and a user-specified analysis method. This design code is called CometBoards, which is an acronym for Comparative Evaluation Test Bed of Optimization and Analysis Routines for the Design of Structures. This manual describes for the user a step-by-step procedure for setting up the input data files and executing CometBoards to solve a structural design problem. The manual includes the organization of CometBoards; instructions for preparing input data files; the procedure for submitting a problem; illustrative examples; and several demonstration problems. A set of 29 structural design problems have been solved by using all the optimization methods available in CometBoards. A summary of the optimum results obtained for these problems is appended to this users manual. CometBoards, at present, is available for Posix-based Cray and Convex computers, Iris and Sun workstations, and the VM/CMS system.

Guptill, James D.↗
DOE OSTI2020

Efficient bi-directional coupling of 3D computational fluid-particle dynamics and 1D Multiple Path Particle Dosimetry lung models for multiscale modeling of aerosol dosimetry

The development of predictive aerosol dosimetry models has been a major focus of environmental toxicology and pharmaceutical health research for decades. One-dimensional (1D) models successfully predict overall deposition averages but fail to accurately predict local deposition. Computational fluid-particle dynamics (CFPD) models provide site-specific predictions but at a computational cost that prohibits whole lung predictions. Thus, there is a need for developing multiscale strategies to provide a realistic subject-specific picture of the fate of inhaled aerosol in the lungs. CT-based 3D/CFPD models of the large airways were bidirectionally coupled with individualized 1D Navier-Stokes airflow and particle transport based upon the widely used Multiple Path Particle Dosimetry Model (MPPD). Distribution of airflows among lobes was adjusted by measured lobar volume changes observed in CT images between FRC and FRC + 1.5 L. Additionally, as a test of the effectiveness of the coupling procedures, deposition modeling of previous 1 µm aerosol exposure studies was performed. The complete coupled model was run for 3 breaths, with the computation-intense portion being the 3D CFD Lagrangian particle tracking calculation. The average deposition per breath was 11% in the combined multiscale model with site-specific doses available in the CFPD portion of the model and airway- or region-specific deposition available for the MPPD portion. In conclusion, the key methods developed in this study enable predictions of ventilation heterogeneities and aerosol deposition across the lungs that are not captured by 3D or 1D models alone. Overall, these methods can be used as the foundation for multi-scale modeling of the full respiratory system.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1977

Development of a procedure to model high-resolution wind profiles from smoothed or low-frequency data

The derivation of simulated Jimsphere wind profiles from low-frequency rawinsonde data and a generated set of white noise data are presented. A computer program is developed to model high-resolution wind profiles based on the statistical properties of data from the Kennedy Space Center, Florida. Comparison of the measured Jimsphere data, rawinsonde data, and the simulated profiles shows excellent agreement.

Camp, D. W.↗
DOE OSTI2015

ProDeGe: A computational protocol for fully automated decontamination of genomes

Single amplified genomes and genomes assembled from metagenomes have enabled the exploration of uncultured microorganisms at an unprecedented scale. However, both these types of products are plagued by contamination. Since these genomes are now being generated in a high-throughput manner and sequences from them are propagating into public databases to drive novel scientific discoveries, rigorous quality controls and decontamination protocols are urgently needed. Here, we present ProDeGe (Protocol for fully automated Decontamination of Genomes), the first computational protocol for fully automated decontamination of draft genomes. ProDeGe classifies sequences into two classes—clean and contaminant—using a combination of homology and feature-based methodologies. On average, 84% of sequence from the non-target organism is removed from the data set (specificity) and 84% of the sequence from the target organism is retained (sensitivity). Lastly, the procedure operates successfully at a rate of ~0.30 CPU core hours per megabase of sequence and can be applied to any type of genome sequence.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2001

Pulse Detonation Engine Modeled

Pulse Detonation Engine Technology is currently being investigated at Glenn for both airbreathing and rocket propulsion applications. The potential for both mechanical simplicity and high efficiency due to the inherent near-constant-volume combustion process, may make Pulse Detonation Engines (PDE's) well suited for a number of mission profiles. Assessment of PDE cycles requires a simulation capability that is both fast and accurate. It should capture the essential physics of the system, yet run at speeds that allow parametric analysis. A quasi-one-dimensional, computational-fluid-dynamics-based simulation has been developed that may meet these requirements. The Euler equations of mass, momentum, and energy have been used along with a single reactive species transport equation, and submodels to account for dominant loss mechanisms (e.g., viscous losses, heat transfer, and valving) to successfully simulate PDE cycles. A high-resolution numerical integration scheme was chosen to capture the discontinuities associated with detonation, and robust boundary condition procedures were incorporated to accommodate flow reversals that may arise during a given cycle. The accompanying graphs compare experimentally measured and computed performance over a range of operating conditions for a particular PDE. Experimental data were supplied by Fred Schauer and Jeff Stutrud from the Air Force Research Laboratory at Wright-Patterson AFB and by Royce Bradley from Innovative Scientific Solutions, Inc. The left graph shows thrust and specific impulse, Isp, as functions of equivalence ratio for a PDE cycle in which the tube is completely filled with a detonable hydrogen/air mixture. The right graph shows thrust and specific impulse as functions of the fraction of the tube that is filled with a stoichiometric mixture of hydrogen and air. For both figures, the operating frequency was 16 Hz. The agreement between measured and computed values is quite good, both in terms of trend and magnitude. The error is under 10 percent everywhere except for the thrust value at an equivalence ratio of 0.8 in the left figure, where it is 14 percent. The simulation results shown were made using 200 numerical cells. Each cycle of the engine, approximately 0.06 sec, required 2.0 min of CPU time on a Sun Ultra2. The simulation is currently being used to analyze existing experiments, design new experiments, and predict performance in propulsion concepts where the PDE is a component (e.g., hybrid engines and combined cycles).

Paxson, Daniel E.↗
DOE OSTI2017

Blast-Wave Characteristics Near Site 300

We have developed a procedure for calculating the maximum high-explosive weight limit for use at Site 300 based on the analysis of the blast-wave propagation behavior in the atmosphere. Both analytical and experimental efforts have been involved in the present work, including a literature search, evaluation of other data, measurements of local weather conditions, and implementation of relevant computational programs. Major results of the present effort are • Comparison of the LLNL data with other data reveals discrepancies, suggesting that local effects, such as weather conditions in the downrange regions, may play a role in affecting the wave-propagation behavior. Our measurements of the local weather conditions indeed show that they differ from those at Site 300. • Analyses of other, newer models and data have resulted in the implementation of relevant computer codes, such as the BLASTO code, to be used at Site 300. • A new procedure for predicting the weight limit at Site 300 has been recommended. This new procedure consists of - Site 300 and local valley weather measurements. - The LAP code. - The BLASTO code. The LAP code is a modified SIPS code and computes the acoustic ray trajectories, including the focus ("caustic") locations, under varying local weather conditions. The BLASTO code calculates the peak overpressure vs distance relationship for a given charge weight and weather condition. Both the LAP code and the BLASTO code have been implemented and are operational at Site 300. Future plans include conducting selective tests to verify the validity of the predictive procedure recommended for Site 300.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
NASA NTRS1972

Computer program of data reduction procedures for facilities using CO2-N2-O2-Ar equilibrium real-gas mixtures

Data reduction procedures for determining free-stream and post-normal-shock flow conditions are presented. These procedures are applicable to flows of CO2, N2, O2, Ar, or mixtures of these gases and include the effects of dissociation and ionization. The assumption of thermochemical equilibrium free-stream and post-normal-shock flow is made. Although derived primarily to meet the immediate needs of an expansion tube of a hot gas radiation research facility, these procedures are applicable to any supersonic or hypersonic test facility using these gases or mixtures thereof. The data reduction procedures are based on combinations of three of the following flow parameters measured in the immediate vicinity of the test section: (1) stagnation pressure behind normal shock, (2) free-stream static pressure, (3) stagnation-point heat-transfer rate, (4) free-stream velocity, and (5) free-stream density. Thus, these procedures do not depend explicitly upon measured or calculated upstream flow parameters. The procedures are incorporated into a single computer program written in FORTRAN IV language. A listing of this computer program is presented, along with a description of the inputs required and a sample of the data printout.

Miller, C. G., III↗
DOE OSTI2015

A high-order vertex-based central ENO finite-volume scheme for three-dimensional compressible flows

High-order discretization methods offer the potential to reduce the computational cost associated with modeling compressible flows. However, it is difficult to obtain accurate high-order discretizations of conservation laws that do not produce spurious oscillations near discontinuities, especially on multi-dimensional unstructured meshes. A novel, high-order, central essentially non-oscillatory (CENO) finite-volume method that does not have these difficulties is proposed for tetrahedral meshes. The proposed unstructured method is vertex-based, which differs from existing cell-based CENO formulations, and uses a hybrid reconstruction procedure that switches between two different solution representations. It applies a high-order k-exact reconstruction in smooth regions and a limited linear reconstruction when discontinuities are encountered. Both reconstructions use a single, central stencil for all variables, making the application of CENO to arbitrary unstructured meshes relatively straightforward. The new approach was applied to the conservation equations governing compressible flows and assessed in terms of accuracy and computational cost. For all problems considered, which included various function reconstructions and idealized flows, CENO demonstrated excellent reliability and robustness. Up to fifth-order accuracy was achieved in smooth regions and essentially non-oscillatory solutions were obtained near discontinuities. The high-order schemes were also more computationally efficient for high-accuracy solutions, i.e., they took less wall time than the lower-order schemes to achieve a desired level of error. In one particular case, it took a factor of 24 less wall-time to obtain a given level of error with the fourth-order CENO scheme than to obtain the same error with the second-order scheme.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Robust scalable initialization for Bayesian variational inference with multi-modal Laplace approximations

Predictive modeling typically relies on Bayesian model calibration to provide uncertainty quantification. Variational inference utilizing fully independent (“mean-field”) Gaussian distributions are often used as approximate probability density functions. This simplification is attractive since the number of variational parameters grows only linearly with the number of unknown model parameters. However, the resulting diagonal covariance structure and unimodal behavior can be too restrictive to provide useful approximations of intractable Bayesian posteriors that exhibit highly non-Gaussian behavior, including multimodality. High-fidelity surrogate posteriors for these problems can be obtained by considering the family of Gaussian mixtures. Gaussian mixtures are capable of capturing multiple modes and approximating any distribution to an arbitrary degree of accuracy, while maintaining some analytical tractability. Unfortunately, variational inference using Gaussian mixtures with full-covariance structures suffers from a quadratic growth in variational parameters with the number of model parameters. The existence of multiple local minima due to strong nonconvex trends in the loss functions often associated with variational inference present additional complications, These challenges motivate the need for robust initialization procedures to improve the performance and computational scalability of variational inference with mixture models. In this work, we propose a method for constructing an initial Gaussian mixture model approximation that can be used to warm-start the iterative solvers for variational inference. The procedure begins with a global optimization stage in model parameter space. In this step, local gradient-based optimization, globalized through multistart, is used to determine a set of local maxima, which we take to approximate the mixture component centers. Around each mode, a local Gaussian approximation is constructed via the Laplace approximation. Finally, the mixture weights are determined through constrained least squares regression. The robustness and scalability of the proposed methodology is demonstrated through application to an ensemble of synthetic tests using high-dimensional, multimodal probability density functions. Here, the practical aspects of the approach are demonstrated with inversion problems in structural dynamics.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2006

Single- and Multiple-Objective Optimization with Differential Evolution and Neural Networks

Genetic and evolutionary algorithms have been applied to solve numerous problems in engineering design where they have been used primarily as optimization procedures. These methods have an advantage over conventional gradient-based search procedures became they are capable of finding global optima of multi-modal functions and searching design spaces with disjoint feasible regions. They are also robust in the presence of noisy data. Another desirable feature of these methods is that they can efficiently use distributed and parallel computing resources since multiple function evaluations (flow simulations in aerodynamics design) can be performed simultaneously and independently on ultiple processors. For these reasons genetic and evolutionary algorithms are being used more frequently in design optimization. Examples include airfoil and wing design and compressor and turbine airfoil design. They are also finding increasing use in multiple-objective and multidisciplinary optimization. This lecture will focus on an evolutionary method that is a relatively new member to the general class of evolutionary methods called differential evolution (DE). This method is easy to use and program and it requires relatively few user-specified constants. These constants are easily determined for a wide class of problems. Fine-tuning the constants will off course yield the solution to the optimization problem at hand more rapidly. DE can be efficiently implemented on parallel computers and can be used for continuous, discrete and mixed discrete/continuous optimization problems. It does not require the objective function to be continuous and is noise tolerant. DE and applications to single and multiple-objective optimization will be included in the presentation and lecture notes. A method for aerodynamic design optimization that is based on neural networks will also be included as a part of this lecture. The method offers advantages over traditional optimization methods. It is more flexible than other methods in dealing with design in the context of both steady and unsteady flows, partial and complete data sets, combined experimental and numerical data, inclusion of various constraints and rules of thumb, and other issues that characterize the aerodynamic design process. Neural networks provide a natural framework within which a succession of numerical solutions of increasing fidelity, incorporating more realistic flow physics, can be represented and utilized for optimization. Neural networks also offer an excellent framework for multiple-objective and multi-disciplinary design optimization. Simulation tools from various disciplines can be integrated within this framework and rapid trade-off studies involving one or many disciplines can be performed. The prospect of combining neural network based optimization methods and evolutionary algorithms to obtain a hybrid method with the best properties of both methods will be included in this presentation. Achieving solution diversity and accurate convergence to the exact Pareto front in multiple objective optimization usually requires a significant computational effort with evolutionary algorithms. In this lecture we will also explore the possibility of using neural networks to obtain estimates of the Pareto optimal front using non-dominated solutions generated by DE as training data. Neural network estimators have the potential advantage of reducing the number of function evaluations required to obtain solution accuracy and diversity, thus reducing cost to design.

Rai, Man Mohan↗
DOE OSTI2018

A mesh-independent method for planar three-dimensional crack growth in finite domains: A mesh-independent method for crack growth in 3D finite domains

The discrete crack mechanics (DCM) method is a dislocation-based crack modeling technique where cracks are constructed using Volterra dislocation loops. The method allows for the natural introduction of displacement discontinuities, avoiding numerically expensive techniques. Mesh dependence in existing computational modeling of crack growth is eliminated by utilizing a superposition procedure. The elastic field of cracks in finite bodies is separated into two parts: the infinite-medium solution of discrete dislocations and an finite element method solution of a correction problem that satisfies external boundary conditions. In the DCM, a crack is represented by a dislocation array with a fixed outer loop determining the crack tip position encompassing additional concentric loops free to expand or contract. Solving for the equilibrium positions of the inner loops gives the crack shape and stress field. The equation of motion governing the crack tip is developed for quasi-static growth problems. Additionally, convergence and accuracy of the DCM method are verified with two- and three-dimensional problems with well-known solutions. Crack growth is simulated under load and displacement (rotation) control. In the latter case, a semicircular surface crack in a bent prismatic beam is shown to change shape as it propagates inward, stopping as the imposed rotation is accommodated.

42 ENGINEERING↗
DOE OSTI2022

Dataset of solution-based inorganic materials synthesis procedures extracted from the scientific literature

The development of a materials synthesis route is usually based on heuristics and experience. A possible new approach would be to apply data-driven approaches to learn the patterns of synthesis from past experience and use them to predict the syntheses of novel materials. However, this route is impeded by the lack of a large-scale database of synthesis formulations. In this work, we applied advanced machine learning and natural language processing techniques to construct a dataset of 35,675 solution-based synthesis procedures extracted from the scientific literature. Each procedure contains essential synthesis information including the precursors and target materials, their quantities, and the synthesis actions and corresponding attributes. Every procedure is also augmented with the reaction formula. Through this work, we are making freely available the first large dataset of solution-based inorganic materials synthesis procedures.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Initial Studies Toward Real-Time Transmission Path Rating

Demand continues to increase while transmission line construction is being constrained by multiple factors— economic, environmental, and political. Effective and efficient utilization of transmission lines is thus of great importance in an open access environment. Large blocks of power are transferred from areas with inexpensive generation to heavy load demand areas or areas with high generation costs. This results in some transmission paths being loaded closer to their path ratings, which limits further power transfer between areas. Traditionally, rating of important paths was determined off line by assuming the worst-case study scenario; once determined, it could be used for years. With increasing uncertainty arising from rapid growth of renewable energy and smart technologies, path rating studies are needed in near-real time to account for the latest system status and support a reliable and economic power grid. This paper adopts a simplified procedure based on standards of the North American Electric Reliability Corporation (NERC) to determine total transfer capability (TTC) or transfer limit for the purpose of demonstrating the benefits and necessity of real-time path rating. Initial studies are conducted to compute TTC of a two-area test system and a 39-bus test system. Results indicate that path rating can be significantly affected by loading conditions, generator schedules, system topology and other factors.

Singh, Ruchi↗
DOE OSTI2016

SU-F-T-266: Dynalogs Based Evaluation of Different Dose Rate IMRT Using DVH and Gamma Index

Purpose: This work investigates the impact of low and high dose rate on IMRT through Dynalogs by evaluating Gamma Index and Dose Volume Histogram. Methods: The Eclipse™ treatment planning software was used to generate plans on prostate and head and neck sites. A range of dose rates 300 MU/min and 600 MU/min were applied to each plan in order to investigate their effect on the beam ON time, efficiency and accuracy. Each plan had distinct monitor units per fraction, delivery time, mean dose rate and leaf speed. The DVH data was used in the assessment of the conformity and plan quality.The treatments were delivered on Varian™ Clinac 2100C accelerator equipped with 120 leaf millennium MLC. Dynalogs of each plan were analyzed by MATLAB™ program. Fluence measurements were performed using the Sun Nuclear™ 2D diode array and results were assessed, based on Gamma analysis of dose fluence maps, beam delivery statistics and Dynalogs data. Results: Minor differences found by adjusted R-squared analysis of DVH’s for all the plans with different dose rates. It has been also found that more and larger fields have greater time reduction at high dose rate and there was a sharp decrease in number of control points observed in dynalog files by switching dose rate from 300 MU/min to 600 MU/min. Gamma Analysis of all plans passes the confidence limit of ≥95% with greater number of passing points in 300 MU/min dose rate plans. Conclusion: The dynalog files are compatible tool for software based IMRT QA. It can work perfectly parallel to measurement based QA setup and stand-by procedure for pre and post delivery of treatment plan.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Development and Demonstration of a Fuel-Efficient, Class 8 Tractor & Trailer Engine System (SuperTruck II)

Navistar presents the SuperTruck II (ST II) Final Report to the Unites States Department of Energy (US DOE), which covers the five Budget Periods (BPs) from 10-1-2016 through 6-30-2022. For ST II, Navistar built on the achievements of the SuperTruck I (ST I) Program as a catalyst to continue critical research, design and development, testing, and operations to reach the ambitious goals of the ST II project. This approach allowed Navistar to continue contributing to the essential needs of our nation for safe, efficient, and cost-effective delivery of goods and services, as we reduced negative environmental effects and improved operational productivity. This document contains information specified in DOE F 4600.2, Final Scientific/Technical Report DOE F 241.3, B. SCIENTIFIC/TECHNICAL REPORTS, explaining how we met and exceeded program requirements. Throughout this Final Report, Navistar extracted information from documents prepared during the project that represent our management, design and development, building, and testing efforts to meet and exceed SuperTruck II project goals. Navistar followed Plan requirements to achieve / exceed Project Objectives: a) >100% improvement in vehicle freight efficiency (FE) (on ton-MPG basis) relative to 2009 baseline with stretch goal of 140% improvement [actual: 170%); b) >55% engine brake thermal efficiency (BTE) demonstrated in operational engine at a 65-mph cruise point on a dynamometer – ≥31% increase from 2009 baseline [actual: 55.20% of combined BTE) ; and c) development and implementation of commercially cost effective technologies (in terms of a simple payback). Technology selection / development path focused on developing technologies applicable for production within 3-year approach, while ensuring technology readiness and cost of ownership for end users. The Program was organized into five budget periods: Requirements / Technology Assessment and Initial Hardware Testing; Technology Development and Concept Readiness Demonstration; Technology Finalization and Validation Tractor / Trailer Fabrication, Integration and Commissioning Demonstration; and Fuel Economy (FE) and Brake Thermal Efficiency (BTE) and Program Completion. Leadership was provided by DOE, with tasks performed by laboratories (Argonne National Laboratory, Lawrence Livermore National Laboratory); partners at Bosch, TPI, Dana, and J.B. Hunt; , and support from University of Michigan and Clemson University. Navistar lead this team with Principal Investigator / Contracting Officer; Project Manager (PM); Vehicle, Engine, and Aftertreatment Engineers; Finance Manager, Technical Program Leads, and Legal/IP; and other key personnel. Work also included personnel in risk management; funding / budget / finance. Work involved analysis, development, testing, and down selection of individual/system engine, aftertreatment, and vehicle technologies, with integration of selected technologies into a prototype vehicle for demonstration of fuel-efficiency gain. Work also included component/integrated system level development of truck and trailer aerodynamics, base engine efficiency, advanced aftertreatment, combustion efficiency, waste heat recovery, hybrid powertrain, reduced rolling resistance, weight reduction, idle reduction, and driver feedback. As ST II progressed, Navistar performed computer-based modeling / simulations of technologies focused on the primary operational areas: Engine, Aftertreatment, and Vehicle. During the ST II Program, the COVID Virus outbreak unexpectedly challenged by the effects of, which affected staffing, scheduling, design, supplies, availability of materials, production procedures, and testing. The DOE responded by extending the program by three quarters to ensure that project tasks were completed for this vital project. Focus continued on analyzing, developing, testing, and down selecting individual-/system-level engine and vehicle technologies for integration of the final selected technologies into a prototype vehicle that would demonstrate fuel-efficiency gains made possible through these technologies. This included component/integrated system-level development of truck and trailer aerodynamics, base engine efficiency, advanced aftertreatment, combustion efficiency, waste heat recovery, solar power, distributed and intelligent vehicle power, hybrid powertrain, reduced rolling resistance, weight reduction, idle reduction, and driver feedback. Throughout the program, function, reliability, and performance at all levels were ensured through testing. Proof of this approach was demonstrated in multiple, on-road demonstrations: Scenario A (Flatland) Fuel Economy, Scenario B (Hilly) Fuel Economy, and City Cycle Tests. Other benefits derived from ST II included new/improved products, publications, patents, and next-step capabilities related to electric/hydrogen vehicles and autonomous driving.

Zukouski, Russ↗
NASA NTRS1971

Proposed techniques for launching instrumented balloons into tornadoes

A method is proposed to introduce instrumented balloons into tornadoes by means of the radial pressure gradient, which supplies a buoyancy force driving to the center. Presented are analytical expressions, verified by computer calculations, which show the possibility of introducing instrumented balloons into tornadoes at or below the cloud base. The times required to reach the center are small enough that a large fraction of tornadoes are suitable for the technique. An experimental procedure is outlined in which a research airplane puts an instrumented, self-inflating balloon on the track ahead of the tornado. The uninflated balloon waits until the tornado closes to, typically, 750 meters; then it quickly inflates and spirals up and into the core, taking roughly 3 minutes. Since the drive to the center is automatically produced by the radial pressure gradient, a proper launch radius is the only guidance requirement.

Grant, F. C.↗
NASA NTRS1977

Estimation of ground temperature from GFCR radiometric signal

A procedure was developed which demonstrates the feasibility of estimating actual surface temperature from the effective brightness temperature which can be conveniently measured by a radiometer from remote sensing platforms. Atmospheric corrections to the effective brightness temperature are computed corresponding to the 'base model' atmosphere and several modifications of this caused by deviations of the various atmospheric or surface parameters from their base model values. Simple analytical relations were established between the deviations of these parameters and the additional temperature corrections required to compensate for them. Effects of simultaneous variation of several parameters also were examined. Use of these analytical relations, instead of radiative transfer calculations, results in tremendous savings in data reduction costs.

Gupia, S. K.↗
NASA NTRS1978

Digital filter structures having low errors and simple hardware implementation

Sensitivity and roundoff errors can seriously limit the application of recursive digital filters in practice, particularly when the filters have poles near z = + 1. A filter structure, based on digital incremental computers is proposed, which has low sensitivity, good error characteristics, and simple hardware implementation for pole locations close to z = + 1. Expressions for the roundoff errors are derived and compared to those for conventional structures. A design procedure is suggested to implement the new filter structure given the transfer function. Simulation results are presented.

Abu-El-haija, A. I.↗