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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Cycle life regression model, cycle life prediction model, and acceleration factors are discussed. A method was presented to: (1) select a mathematical model; (2) determine model coefficients using accelerated test data; (3) test model fit of the accelerated test data; and (4) predict normal packs.
The successful application of statistical variable selection techniques to fit splines is demonstrated. Major emphasis is given to knot selection, but order determination is also discussed. Two FORTRAN backward elimination programs, using the B-spline basis, were developed. The program for knot elimination is compared in detail with two other spline-fitting methods and several statistical software packages. An example is also given for the two-variable case using a tensor product basis, with a theoretical discussion of the difficulties of their use.
A catalog of energy management models for heavy duty transport systems powered by diesel engines is presented. The catalog results from a literature survey, supplemented by telephone interviews and mailed questionnaires to discover the major computer models currently used in the transportation industry in the following categories: heavy duty transport systems, which consist of highway (vehicle simulation), marine (ship simulation), rail (locomotive simulation), and pipeline (pumping station simulation); and heavy duty diesel engines, which involve models that match the intake/exhaust system to the engine, fuel efficiency, emissions, combustion chamber shape, fuel injection system, heat transfer, intake/exhaust system, operating performance, and waste heat utilization devices, i.e., turbocharger, bottoming cycle.
The goal of the research described is to develop flexible language constructs for writing large data parallel numerical programs for distributed memory (MIMD) multiprocessors. Previously, several models have been developed to support synchronization and communication. Models for global synchronization include SIMD (Single Instruction Multiple Data), SPMD (Single Program Multiple Data), and sequential programs annotated with data distribution statements. The two primary models for communication include implicit communication based on shared memory and explicit communication based on messages. None of these models by themselves seem sufficient to permit the natural and efficient expression of the variety of algorithms that occur in large scientific computations. An overview of a new language that combines many of these programming models in a clean manner is given. This is done in a modular fashion such that different models can be combined to support large programs. Within a module, the selection of a model depends on the algorithm and its efficiency requirements. An overview of the language and discussion of some of the critical implementation details is given.
An investigation has been made to study boundary-layer transition on six axisymmetrical blunt bodies of revolution. Model shapes were selected with respect to the degree of favorable pressure gradient over the model surface. Tests were conducted at a Mach number of 2.20 and over a range of free-stream Reynolds number per foot of about 1.4 x 10(exp 6) to 6.5 x 10(exp 6). The tests were made at an angle of attack of 0 deg. with zero heat transfer. For the hemisphere, the flow remained essentially laminar over the model surface length for the entire pressure range of the tests. For a strong favorable pressure gradient followed by any weak favorable, neutral, or adverse gradient, the tendency was for transition to occur at or immediately behind the shoulder. A single strip of three-dimensional roughness in the region of strong favorable pressure gradient did not fix transition on the models at the roughness location except at the maximum test pressures, whereas a second roughness strip added in a region of neutral or adverse pressure gradient did fix transition. Experimental pressure coefficients agreed closely with modified Newtonian theory except in the shoulder region.
Many urban hospitals are becoming overloaded with drug abuse cases requiring chemical analysis for identification of drugs. In this paper, the requirements for chemical analysis of body fluids for drugs are determined and a system model for automated drug analysis is selected. The system as modeled, would perform chemical preparation of samples, gas-liquid chromatographic separation of drugs in the chemically prepared samples, infrared spectrophotometric analysis of the drugs, and would utilize automatic data processing and control for drug identification. Requirements of cost, maintainability, reliability, flexibility, and operability are considered.
This study established two- and three-dimensional renal proximal tubular cell cultures of the endangered species bowhead whale (Balaena mysticetus), developed SV40-transfected cultures, and cloned the 61-amino acid open reading frame for the metallothionein protein, the primary binding site for heavy metal contamination in mammals. Microgravity research, modulations in mechanical culture conditions (modeled microgravity), and shear stress have spawned innovative approaches to understanding the dynamics of cellular interactions, gene expression, and differentiation in several cellular systems. These investigations have led to the creation of ex vivo tissue models capable of serving as physiological research analogs for three-dimensional cellular interactions. These models are enabling studies in immune function, tissue modeling for basic research, and neoplasia. Three-dimensional cellular models emulate aspects of in vivo cellular architecture and physiology and may facilitate environmental toxicological studies aimed at elucidating biological functions and responses at the cellular level. Marine mammals occupy a significant ecological niche (72% of the Earth's surface is water) in terms of the potential for information on bioaccumulation and transport of terrestrial and marine environmental toxins in high-order vertebrates. Few ex vivo models of marine mammal physiology exist in vitro to accomplish the aforementioned studies. Techniques developed in this investigation, based on previous tissue modeling successes, may serve to facilitate similar research in other marine mammals.
This study established two- and three-dimensional renal proximal tubular cell cultures of the endangered species bowhead whale (Balaena mysticetus), developed SV40-transfected cultures, and cloned the 61-amino acid open reading frame for the metallothionein protein, the primary binding site for heavy metal contamination in mammals. Microgravity research, modulations in mechanical culture conditions (modeled microgravity), and shear stress have spawned innovative approaches to understanding the dynamics of cellular interactions, gene expression, and differentiation in several cellular systems. These investigations have led to the creation of ex vivo tissue models capable of serving as physiological research analogs for three-dimensional cellular interactions. These models are enabling studies in immune function, tissue modeling for basic research, and neoplasia. Three-dimensional cellular models emulate aspects of in vivo cellular architecture and physiology and may facilitate environmental toxicological studies aimed at elucidating biological functions and responses at the cellular level. Marine mammals occupy a significant ecological niche (72% of the Earth's surface is water) in terms of the potential for information on bioaccumulation and transport of terrestrial and marine environmental toxins in high-order vertebrates. Few ex vivo models of marine mammal physiology exist in vitro to accomplish the aforementioned studies. Techniques developed in this investigation, based on previous tissue modeling successes, may serve to facilitate similar research in other marine mammals.
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The co-expression extrapolation (COXEN) method has been successfully used in multiple studies to select genes for predicting the response of tumor cells to a specific drug treatment. Here, we enhance the COXEN method to select genes that are predictive of the efficacies of multiple drugs for building general drug response prediction models that are not specific to a particular drug. The enhanced COXEN method first ranks the genes according to their prediction power for each individual drug and then takes a union of top predictive genes of all the drugs, among which the algorithm further selects genes whose co-expression patterns are well preserved between cancer cases for building prediction models. We apply the proposed method on benchmark in vitro drug screening datasets and compare the performance of prediction models built based on the genes selected by the enhanced COXEN method to that of models built on genes selected by the original COXEN method and randomly picked genes. Models built with the enhanced COXEN method always present a statistically significantly improved prediction performance (adjusted p-value ≤ 0.05). Our results demonstrate the enhanced COXEN method can dramatically increase the power of gene expression data for predicting drug response.
A candidate math model search algorithm was developed at Ames Research Center that determines a recommended math model for the multivariate regression analysis of experimental data. The search algorithm is applicable to classical regression analysis problems as well as wind tunnel strain gage balance calibration analysis applications. The algorithm compares the predictive capability of different regression models using the standard deviation of the PRESS residuals of the responses as a search metric. This search metric is minimized during the search. Singular value decomposition is used during the search to reject math models that lead to a singular solution of the regression analysis problem. Two threshold dependent constraints are also applied. The first constraint rejects math models with insignificant terms. The second constraint rejects math models with near-linear dependencies between terms. The math term hierarchy rule may also be applied as an optional constraint during or after the candidate math model search. The final term selection of the recommended math model depends on the regressor and response values of the data set, the user s function class combination choice, the user s constraint selections, and the result of the search metric minimization. A frequently used regression analysis example from the literature is used to illustrate the application of the search algorithm to experimental data.
The Department of Energy and the National Cancer Institute have developed new software for conducting multi-scale simulations of complex systems. This software, called the Multiscale Machine-Learned Modeling Infrastructure (MuMMI), couples simulations on three spatial scales to study slow, large-scale reorganizations of biomolecular systems with the speed of continuum and coarse-grained models while revealing selected interactions at full atomic precision. In these simulations, coarse-to-fine model conversions are used to spawn relevant fine-scale simulations along chosen order parameters, and fine-to-coarse feedback is used to iteratively improve the accuracy and multi-scale consistency of coarse-scale and continuum simulations. The complete MuMMI framework will be reviewed and released as open-source software by Lawrence Livermore National Laboratory. This review covers a subset of the MuMMI components that were developed exclusively at the Los Alamos National Laboratory.
Methods for reduction of velocities in trailing vortices of large aircraft are of current interest for the purpose of shortening the waiting time between landings at central airports. We have made finite-difference calculations of the flow in turbulent wake vortices as an aid to interpretation of wind-tunnel and flight experiments directed toward that end. Finite-difference solutions are capable of adding flexibility to such investigations if they are based on an adequate model of turbulence. Interesting developments have been taking place in the knowledge of turbulence that may lead to a complete theory in the future. In the meantime, approximate methods that yield reasonable agreement with experiment are appropriate. The simplified turbulence model we have selected contains features that account for the major effects disclosed by more sophisticated models in which the parameters are not yet established. Several puzzles are thereby resolved that arose in previous theoretical investigations of wake vortices.
A nonlinear modeling technique was used to characterize response surfaces for non-dimensional longitudinal aerodynamic force and moment coefficients, based on wind tunnel data from a commercial jet transport model. Data were collected using two experimental procedures - one based on modem design of experiments (MDOE), and one using a classical one factor at a time (OFAT) approach. The nonlinear modeling technique used multivariate orthogonal functions generated from the independent variable data as modeling functions in a least squares context to characterize the response surfaces. Model terms were selected automatically using a prediction error metric. Prediction error bounds computed from the modeling data alone were found to be- a good measure of actual prediction error for prediction points within the inference space. Root-mean-square model fit error and prediction error were less than 4 percent of the mean response value in all cases. Efficacy and prediction performance of the response surface models identified from both MDOE and OFAT experiments were investigated.
While devoid of an active magnetic dynamo field today, Mars possesses a remanent magnetic field that may reach several thousand nanoteslas locally. The exact origin and the events that have shaped the crustal magnetization remain largely enigmatic. Three magnetic field data sets from two spacecraft collected over 13 cumulative years have sampled the Martian magnetic field over a range of altitudes from 90 up to 6,000 km: (a) Mars Global Surveyor (MGS) magnetometer (1997–2006), (b) MGS Electron Reflectometer (1999–2006), and (c) Mars Atmosphere and Volatile EvolutioN (MAVEN) magnetometer (2014 to today). In this paper we combine these complementary data sets for the first time to build a new model of the Martian internal magnetic field. This new model improves upon previous ones in several aspects: comprehensive data coverage, refined data selection scheme, modified modeling scheme, discrete-to-continuous transformation of the model, and increased model resolution. The new model has a spatial resolution of ∼160 km at the surface, corresponding to spherical harmonic degree 134. It shows small scales and well-defined features, which can now be associated with geological signatures.
This report provides a description of the basis for the development and implementation of a conceptual model for vadose zone flow and transport for the Hanford Site composite analysis (CA) groundwater pathway analysis. The parameterization for a numerical model is intimately linked to the conceptual model framework. This report describes the basis for the selection of hydraulic and transport parameters for the hydrostratigraphic units (HSUs) identified in the 200 East and 200 West Areas. The following three-step process was used to develop the hydraulic properties and transport parameters for the CA modeling: 1. Breakdown of existing database on hydraulic properties by HSUs 2. Constitutive model parameters for laboratory, core-scale hydraulic properties 3. Upscaling for macroscopic, field-scale flow, and transport parameters This document provides data and information on the following items: A brief description and technical basis for the conceptual model selected to represent vadose zone flow and transport for the CA modeling. Variation in sediment particle size distribution for representative sites in the 200 East and West Areas. A summary of effective (upscaled) moisture retention, and saturated and unsaturated hydraulic conductivity estimates for the HSUs in the 200 East and West Areas. A summary of effective transport parameters, including sediment bulk density and macrodispersivity estimates for various HSUs. The 200 East Area B Complex perched water aquifer hydraulic properties
NASA's Environmentally Responsible Aviation Project and Subsonic Fixed Wing Project are focused on developing concepts and technologies which may enable dramatic reductions to the environmental impact of future generation subsonic aircraft (Refs. 1 and 2). The open rotor concept (also referred to as the Unducted Fan or advanced turboprop) may allow the achievement of this objective by reducing engine emissions and fuel consumption. To evaluate its potential impact, an open rotor cycle modeling capability is needed. This paper presents the initial development of an open rotor cycle model in the Numerical Propulsion System Simulation (NPSS) computer program which can then be used to evaluate the potential benefit of this engine. The development of this open rotor model necessitated addressing two modeling needs within NPSS. First, a method for evaluating the performance of counter-rotating propellers was needed. Therefore, a new counter-rotating propeller NPSS component was created. This component uses propeller performance maps developed from historic counter-rotating propeller experiments to determine the thrust delivered and power required. Second, several methods for modeling a counter-rotating power turbine within NPSS were explored. These techniques used several combinations of turbine components within NPSS to provide the necessary power to the propellers. Ultimately, a single turbine component with a conventional turbine map was selected. Using these modeling enhancements, an open rotor cycle model was developed in NPSS using a multi-design point approach. The multi-design point (MDP) approach improves the engine cycle analysis process by making it easier to properly size the engine to meet a variety of thrust targets throughout the flight envelope. A number of design points are considered including an aerodynamic design point, sea-level static, takeoff and top of climb. The development of this MDP model was also enabled by the selection of a simple power management scheme which schedules propeller blade angles with the freestream Mach number. Finally, sample open rotor performance results and areas for further model improvements are presented.
The purpose is to introduce certain models of topology selective stochastic jamming and examine its impact on a class of fully-connected, spread-spectrum, slotted ALOHA-type random access networks. The theory covers dedicated as well as half-duplex units. The dominant role of the spatial duty factor is established, and connections with the dual concept of time selective jamming are discussed. The optimal choices of coding rate and link access parameters (from the users' side) and the jamming spatial fraction are numerically established for DS and FH spreading.