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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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The Computational Structural Mechanics (CSM) program at Lewis encompasses: (1) fundamental aspects for formulating and solving structural mechanics problems, and (2) development of integrated software systems to computationally simulate the performance/durability/life of engine structures.
Computer system controls start-up, steady-state operation, throttling, and shutdown of pair of xenon-ion propulsion engines. Controls direction of thrust of each engine through operation of gimbal stepping motors. Controls valves in propellant-storage and propellant-distribution system. Control software establishes and maintains efficient, stable operation over entire range of operating variables, and throttles engines to any point within range. Computer operates power supplies, valves, and flow controllers of two ion engines, ion-neutralizer subsystem, and other equipment. Designed for use in interplanetary flight, system adaptable to industrial use in ion-beam deposition of thin films.
Engineers are constantly faced with solving problems of increasing complexity and detail. Multiple Instruction stream Multiple Data stream (MIMD) computers have been developed to overcome the performance limitations of serial computers. The hardware architectures of MIMD computers vary considerably and are much more sophisticated than serial computers. Developing large scale software for a variety of MIMD computers is difficult and expensive. There is a need to provide tools that facilitate programming these machines. First, the issues that must be considered to develop those tools are examined. The two main areas of concern were architecture independence and data management. Architecture independent software facilitates software portability and improves the longevity and utility of the software product. It provides some form of insurance for the investment of time and effort that goes into developing the software. The management of data is a crucial aspect of solving large engineering problems. It must be considered in light of the new hardware organizations that are available. Second, the functional design and implementation of a software environment that facilitates developing architecture independent software for large engineering applications are described. The topics of discussion include: a description of the model that supports the development of architecture independent software; identifying and exploiting concurrency within the application program; data coherence; engineering data base and memory management.
A modern launch vehicle is by necessity an extremely integrated design. The accurate characterization of its aerodynamic characteristics is essential to determine design loads, to design flight control laws, and to establish performance. The NASA Ares Aerodynamics Panel has been responsible for technical planning, execution, and vetting of the aerodynamic characterization of the Ares I vehicle. An aerodynamics team supporting the Panel consists of wind tunnel engineers, computational engineers, database engineers, and other analysts that address topics such as uncertainty quantification. The team resides at three NASA centers: Langley Research Center, Marshall Space Flight Center, and Ames Research Center. The Panel has developed strategies to synergistically combine both the wind tunnel efforts and the computational efforts with the goal of validating the computations. Selected examples highlight key flow physics and, where possible, the fidelity of the comparisons between wind tunnel results and the computations. Lessons learned summarize what has been gleaned during the project and can be useful for other vehicle development projects.
Computational system comprising modular hardware and software sub-systems developed to accelerate and facilitate use of techniques of computational fluid dynamics (CFD) in engineering environment. Addresses integration of all aspects of CFD analysis process, including definition of hardware surfaces, generation of computational grids, CFD flow solution, and postprocessing. Incorporates interfaces for integration of all hardware and software tools needed to perform complete CFD analysis. Includes tools for efficient definition of flow geometry, generation of computational grids, computation of flows on grids, and postprocessing of flow data. System accepts geometric input from any of three basic sources: computer-aided design (CAD), computer-aided engineering (CAE), or definition by user.
Computer simulation developed to study advantages of increased exhaust enthalpy in adiabatic turbocompounded diesel engine. Subsytems of conceptual engine include compressor, reciprocator, turbocharger turbine, compounded turbine, ducting, and heat exchangers. Focus of simulation of total system is to define transfers of mass and energy, including release and transfer of heat and transfer of work in each subsystem, and relationship among subsystems. Written in FORTRAN IV.
Analog/hybrid computers in university engineering education
Analog/hybrid computers as live mathematical model teaching aids in engineering education
The Weight Analysis of Turbine Engines (WATE) computer code was developed by Boeing under contract to NASA Lewis. It was designed to function as an adjunct to the Navy/NASA Engine Program (NNEP). NNEP calculates the design and off-design thrust and sfc performance of User defined engine cycles. The thermodynamic parameters throughout the engine as generated by NNEP are then combined with input parameters defining the component characteristics in WATE to calculate the bare engine weight of this User defined engine. Preprocessor programs for NNEP were previously developed to simplify the task of creating input datasets. This report describes a similar preprocessor for the WATE code.
Computational modeling of the plasma located in the discharge chamber of an ion engine is an important activity so that the development and design of the next generation of ion engines may be enhanced. In this work a computational tool called XOOPIC is used to model the primary electrons, secondary electrons, and ions inside the discharge chamber. The details of this computational tool are discussed in this paper. Preliminary results from XOOPIC are presented. The results presented include particle number density distributions for the primary electrons, the secondary electrons, and the ions. In addition the total number of a particular particle in the discharge chamber as a function of time, electric potential maps and magnetic field maps are presented. A primary electron number density plot from PRIMA is given in this paper so that the results of XOOPIC can be compared to it. PRIMA is a computer code that the present investigators have used in much of their previous work that provides results that compare well to experimental results. PRIMA only models the primary electrons in the discharge chamber. Modeling ions and secondary electrons, as well as the primary electrons, will greatly increase our ability to predict different characteristics of the plasma discharge used in an ion engine.
Digital engineering (DE) and integrated computational materials engineering (ICME) are widely recognized as critical enablers of faster, more affordable, and more reliable aerospace systems. However, many organizations have struggled to realize the promised return on investment (ROI) from digital initiatives. A primary reason is the absence of a shared, decision-focused framework that distinguishes simple digitization of existing workflows from true digital transformation that fundamentally changes how engineering decisions are made. This paper introduces an ICME capability maturity framework that fills this gap. The framework defines six cumulative ICME capability maturity levels (CMLs), explicitly tied to decision authority, engineering integration, optimization, and uncertainty management across material, process, structure, and performance scales. It is designed to complement established readiness metrics such as technology readiness levels (TRLs), manufacturing readiness levels (MRLs), and integration readiness levels (IRLs), by addressing a missing dimension: the conditions required for model-informed decision authority across scales. A unifying figure and capability table illustrate the six-level ICME Capability Maturity Framework, showing how organizations progress from digitization—with limited or negative ROI—to true digital transformation, where ICME-enabled workflows deliver measurable improvements in decision quality, cycle time, risk reduction, and reuse. The framework is intended for both technical practitioners and executive leadership, providing a common language to assess current state, guide roadmaps, align software ecosystem investments, and set realistic expectations for digital transformation outcomes. A regulatory-relevant statement clarifying the relationship between ICME capability and existing certification frameworks is provided.
At Goddard, engineers and scientists with a range of experience in science data systems are needed to employ new technologies and develop advances in capabilities for supporting new Earth and Space science research. Engineers with extensive experience in science data, software engineering and computer-information architectures are needed to lead and perform these activities. The increasing types and complexity of instrument data and emerging computer technologies coupled with the current shortage of computer engineers with backgrounds in science has led the need to develop a career path for science data systems engineers and architects.The current career path, in which undergraduate students studying various disciplines such as Computer Engineering or Physical Scientist, generally begins with serving on a development team in any of the disciplines where they can work in depth on existing Goddard data systems or serve with a specific NASA science team. There they begin to understand the data, infuse technologies, and begin to know the architectures of science data systems. From here the typical career involves peermentoring, on-the-job training or graduate level studies in analytics, computational science and applied science and mathematics. At the most senior level, engineers become subject matter experts and system architect experts, leading discipline-specific data centers and large software development projects. They are recognized as a subject matter expert in a science domain, they have project management expertise, lead standards efforts and lead international projects. A long career development remains necessary not only because of the breadth of knowledge required across physical sciences and engineering disciplines, but also because of the diversity of instrument data being developed today both by NASA and international partner agencies and because multidiscipline science and practitioner communities expect to have access to all types of observational data.This paper describes an approach to defining career-path guidance for college-bound high school and undergraduate engineering students, junior and senior engineers from various disciplines.
The computation of engineering data from finite element solutions based on the virtual work formulation is discussed. It is shown that, using specially chosen virtual displacement functions, it is possible to compute certain functionals from the virtual work expression with much greater efficiency than would be possible by direct methods.
PCACE computer program developed to provide inexpensive, interactive system for learning and using engineering approach to interconnection systems. Basically database system that stores information as files of individual connectors and handles wiring information in circuit groups stored as records. Directly emulates typical manual engineering methods of handling data, thus making interface between user and program very natural. Apple version written in P-Code Pascal and IBM PC version of PCACE written in TURBO Pascal 3.0
The cost of implementing new technology in aerospace propulsion systems is becoming prohibitively expensive. One of the major contributors to the high cost is the need to perform many large scale system tests. Extensive testing is used to capture the complex interactions among the multiple disciplines and the multiple components inherent in complex systems. The objective of the Numerical Propulsion System Simulation (NPSS) is to provide insight into these complex interactions through computational simulations. This will allow for comprehensive evaluation of new concepts early in the design phase before a commitment to hardware is made. It will also allow for rapid assessment of field-related problems, particularly in cases where operational problems were encountered during conditions that would be difficult to simulate experimentally. The tremendous progress taking place in computational engineering and the rapid increase in computing power expected through parallel processing make this concept feasible within the near future. However it is critical that the framework for such simulations be put in place now to serve as a focal point for the continued developments in computational engineering and computing hardware and software. The NPSS concept which is described below will provide that framework.
The cost of implementing new technology in aerospace propulsion systems is becoming prohibitively expensive. One of the major contributors to the high cost is the need to perform many large scale system tests. Extensive testing is used to capture the complex interactions among the multiple disciplines and the multiple components inherent in complex systems. The objective of the Numerical Propulsion System Simulation (NPSS) is to provide insight into these complex interactions through computational simulations. This will allow for comprehensive evaluation of new concepts early in the design phase before a commitment to hardware is made. It will also allow for rapid assessment of field-related problems, particularly in cases where operational problems were encountered during conditions that would be difficult to simulate experimentally. The tremendous progress taking place in computational engineering and the rapid increase in computing power expected through parallel processing make this concept feasible within the near future. However it is critical that the framework for such simulations be put in place now to serve as a focal point for the continued developments in computational engineering and computing hardware and software. The NPSS concept which is described will provide that framework.
Computer simulation results are presented for advanced automobile diesel engine performance. Four critical factors for performance enhancement were identified: (1) part load preheating and exhaust gas energy recovery, (2) fast heat release combustion process, (3) reduction in friction, and (4) air handling system efficiency. Four different technology levels were considered in the analysis. Simulation results are compared in terms of brake specific fuel consumption and vehicle fuel economy in km/liter (miles per gallon). Major critical performance sensitivity areas are: (1) combustion process, (2) expander and compressor efficiency, and (3) part load preheating and compound system. When compared to the state of the art direct injection, cooled, automobile diesel engine, the advanced adiabatic compound engine concept showed the unique potential of doubling the fuel economy. Other important performance criteria such as acceleration, emissions, reliability, durability and multifuel capability are comparable to or better than current passenger car diesel engines.
The Computer-Aided Systems Engineering and Analysis tool used by NASA for environmental control and life support system design studies is capable of simulating atmospheric revitalization systems, water recovery and management systems, and single-phase active thermal control systems. The designer/analysis interface used is graphics-based, and allows the designer to build a model by constructing a schematic of the system under consideration. Data management functions are performed, and the program is translated into a format that is compatible with the solution routines.