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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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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Validated Feasibility Study of Integrally Stiffened Metallic Fuselage Panels for Reducing Manufacturing Costs

The continual need to reduce airframe cost and the emergence of high speed machining and other manufacturing technologies has brought about a renewed interest in large-scale integral structures for aircraft applications. Applications have been inhibited, however, because of the need to demonstrate damage tolerance, and by cost and manufacturing risks associated with the size and complexity of the parts. The Integral Airframe Structures (IAS) Program identified a feasible integrally stiffened fuselage concept and evaluated performance and manufacturing cost compared to conventional designs. An integral skin/stiffener concept was produced both by plate hog-out and near-net extrusion. Alloys evaluated included 7050-T7451 plate, 7050-T74511 extrusion, 6013-T6511 extrusion, and 7475-T7351 plate. Mechanical properties, structural details, and joint performance were evaluated as well as repair, static compression, and two-bay crack residual strength panels. Crack turning behavior was characterized through panel tests and improved methods for predicting crack turning were developed. Manufacturing cost was evaluated using COSTRAN. A hybrid design, made from high-speed machined extruded frames that are mechanically fastened to high-speed machined plate skin/stringer panels, was identified as the most cost-effective manufacturing solution. Recurring labor and material costs of the hybrid design are up to 61 percent less than the current technology baseline.

Pettit, R. G.↗
NASA NTRS1980

Cogeneration Technology Alternatives Study (CTAS). Volume 3: Energy conversion system characteristics

Six current and thirty-six advanced energy conversion systems were defined and combined with appropriate balance of plant equipment. Twenty-six industrial processes were selected from among the high energy consuming industries to serve as a frame work for the study. Each conversion system was analyzed as a cogenerator with each industrial plant. Fuel consumption, costs, and environmental intrusion were evaluated and compared to corresponding traditional values. The advanced energy conversion technologies indicated reduced fuel consumption, costs, and emissions. Fuel energy savings of 10 to 25 percent were predicted compared to traditional on site furnaces and utility electricity. With the variety of industrial requirements, each advanced technology had attractive applications. Fuel cells indicated the greatest fuel energy savings and emission reductions. Gas turbines and combined cycles indicated high overall annual savings. Steam turbines and gas turbines produced high estimated returns. In some applications, diesels were most efficient. The advanced technologies used coal derived fuels, or coal with advanced fluid bed combustion or on site gasifications. Data and information for both current and advanced energy conversion technology are presented. Schematic and physical descriptions, performance data, equipment cost estimates, and predicted emissions are included. Technical developments which are needed to achieve commercialization in the 1985-2000 period are identified.

Source record↗
NASA NTRS1983

Assessment of a 3-D boundary layer code to predict heat transfer and flow losses in a turbine

The prediction of the complete flow field in a turbine passage is an extremely difficult task due to the complex three dimensional pattern which contains separation and attachment lines, a saddle point and horseshoe vortex. Whereas, in principle such a problem can be solved using full Navier-Stokes equations, in reality methods based on a Navier-Stokes solution procedure encounter difficulty in accurately predicting surface quantities (e.g., heat transfer) due to grid limitations imposed by the speed and size of the existing computers. On the other hand the overall problem is strongly three dimensional and too complex to be analyzed by the current design methods based on inviscid and/or viscous strip theories. Thus there is a strong need for enhancing the current prediction techniques through inclusion of 3-D viscous effects. A potentially simple and cost effective way to achieve this is to use a prediction method based on three dimensional boundary layer (3-DBL) theory. The major objective of this program is to assess the applicability of such a 3-DBL approach for the prediction of heat loads, boundary layer growth, pressure losses and streamline skewing in critical areas of a turbine passage. A brief discussion of the physical problem addressed here along with the overall approach is presented.

Vatsa, V. N.↗
NASA NTRS2019

Recommendations for Future Efforts in RANS Modeling and Simulation

The roadmap laid out in the CFD Vision 2030 document suggests that a decision to move away from RANS research needs to be made in the current timeframe (around 2020). This paper outlines industry requirements for improved predictions of turbulent flows and the cost-barrier that is often associated with reliance on scale resolving methods. Capabilities of RANS model accuracy for simple and complex flow flow fields are assessed, and modeling practices that degrade predictive accuracy are identified. Suggested research topics are identified that have the potential to improve the applicability and accuracy of RANS models. We conclude that it is important that some part of a balanced turbulence modeling research portfolio should include RANS efforts.

Bush, Robert H.↗
NASA NTRS1984

An experimental investigation of cusped magnetic field discharge chambers

Several features of a proposed model of ion thruster performance are tested experimentally. The experiment conducted demonstrates the effects of variation in thruster operating parameters on the average plasma ion energy costs and extracted ion fractions of various ring and line cusp discharge chambers. The results indicate that the model correctly predicts the variation in the plasma ion energy cost resulting from changes in: propellant gas, grid transparency to neutral atoms, beam extraction area, and discharge voltage. In addition, the model is shown to be applicable to both ring and line cusp designs. Measurements of the extracted ion fraction indicate that this parameter tends to increase with decreasing discharge voltage and is generally higher for operation with argon as opposed to krypton propellant. Results suggest that to use the proposed thruster performance model as an aid in thruster design the performance may be described in terms of four thruster configuration dependent constants and two operating parameters.

Brophy, J. R.↗
NASA NTRSDate not supplied

ASCoT 3: Nonlinear Principal Components Analysis and Uncertainty Quantification in Early Concept Spacecraft Flight Software Cost Estimation

For mission planners and evaluators alike, value in cost models comes from a mean or median prediction, an understanding of the uncertainty on that prediction, and an understanding of model performance. Here we apply advanced statistical and machine learning methods to spacecraft flight software cost, effort, and SLOC estimation, and present the results in the latest version of the Analogy Software Cost Tool (ASCoT). We present in- and out-of-sample performance metrics for our models, each of which incorporate some amount of epistemic uncertainty. ASCoT, hosted on the One NASA Cost Engineering (ONCE) database via the Online NASA Space Estimation Tool (ONSET), was first showcased in 2016 as a number of analogy-based models and methods (kNN and Clustering) to support early project formulation. This ASCoT update improves upon the previous analogic methods by incorporating uncertainty in the data transformations. In particular, we use a Nonlinear Principal Components Analysis (NLPCA) to deal with ordinal data.

Robotic Spacecraft↗
NASA NTRSDate not supplied

Combining Data with Physical Knowledge for Uncertainty Quantification in Certification and Reliability Analysis

Unifying empirical data with predictive models can enable engineering cost-savings through certification by analysis and reliability-based design. Both concepts require rigorous uncertainty quantification (UQ) and robust understanding and treatment of relevant physics. Combining sampling-based UQ algorithms with high-fidelity simulations creates a computational bottleneck that is often alleviated through the use of machine learning (ML). ML can be used to create computationally efficient surrogates for simulations of complex or high-dimensional physical interactions (e.g., multi-phase interactions associated with melt pools in laser powder bed fusion or spatially-dependent material properties in functionally graded materials). However, negative side effects of ML may include a lack of interpretability and negative correlation between event rarity and simulation accuracy due to a lack of training data. As such, it is important to infuse ML algorithms with physics-based guardrails to provide confidence in their predictions. This talk will provide a brief review of recent NASA research at this intersection of physics-based simulation, ML, and UQ with a focus on certification and reliability analysis.

uncertainty quantification↗
NASA NTRSDate not supplied

EVA Planning: Using Neutral Buoyancy Laboratory (NBL) Training to Predict in-Flight Energy Expenditure

Metabolic rate (“met rate”) is the amount of energy expended over a period of time and is influenced by many factors including body composition, level of physical activity, resting metabolic rate, sex, age, and food intake. Met rate is measured during Extravehicular Activity (EVA) training at the Neutral Buoyancy Laboratory (NBL) and during in-flight EVAs through indirect calorimetry, calculating energy expenditure from respiratory measurements of O 2 consumption and/or CO 2 production. During Extravehicular Activity (EVA) planning, metabolic cost is important to consider and is used to inform EVA duration based on spacesuit consumables associated with life support systems. Currently, NBL and previous ISS EVA met rate data for specified crewmembers are utilized to predict in-flight EVA metabolic costs based on a proposed EVA timeline. Timeline data collected during training is used to relate met rates to specific EVA activities, which are in turn assigned to more generalized EVA task categories, categorizing by both task type and restraint type. EVA task categories include EVA Setup/Cleanup, Worksite Setup/Cleanup, Cable Routing, Bolts, Fluid Connectors, Electrical Connectors, R&R Work, Miscellaneous Work, Incapacitated Crew Rescue (being rescued or performing), Assisted Crew Rescue (being assisted or performing), and Translation. Restraint types consist of Free-Float, Body Restraint Tether (BRT), Articulating Portable Foot Restraint (APFR), and Space Station Remote Manipulator System (SSRMS). From a crewmember’s historical data, individualized 10th, 50th and 90th percentile met rate estimates are generated for each task category and used to estimate the proposed EVA timeline metabolic cost. In-flight metabolic data (“As-Executed”) from recent ISS US EVAs 85-88 (totaling eight EVA crewmember met rates) was compared with their predicted metabolic cost (“As-Planned”) to evaluate the accuracy of the current met rate estimation method. Across the four EVAs, As-Executed Cumulative EVA Total Metabolic Cost (M = 5893.78 BTU, SD = 816.60) was not significantly different compared to As-Planned Cumulative EVA Total Metabolic Cost (M = 6106.60 BTU, SD = 826.62; t(7) = 0.751 , p = .477). Though not a significant difference, generally, As-Planned total estimates were slightly higher than As-Executed total metabolic cost. Relative Error for Cumulative EVA Total Metabolic Cost ranged from -33% to 14.7%, depending on the crewmember and EVA. When comparing As-Planned to A-Executed EVA task categories for Bolts, Electrical Connectors, EVA Cleanup, EVA Setup, Miscellaneous Work, Translation, Worksite Cleanup, and Worksite Setup during these EVAs, no significant differences were observed, however, there was a significant difference in As-Planned (M = 783.71 BTU, SD = 408.88) compared to As-Executed (M = 608.87 BTU, SD = 425.29) metabolic cost for the task category of Repair-and-Replace (R&R) Work (t(17) = 3.21 , p = .005). Looking closer within the R&R Work task category, As-Executed R&R Work with Free-Float restraint type (M = 706.17 BTU, SD = 352.18) was significantly less than As-Planned R&R Work with Free-Float restraint type (M= 887.96 BTU, SD = 381.42; t(12) = 2.59, p < .024). As-Executed R&R Work with SSRMS Restraint type (M = 355.89 BTU, SD = 534.65) was not significantly different from As-Planned values (M = 512.69 BTU, SD = 383.34; t(4) = 1.88, p = 0.132). These findings suggest that the energy expended performing R&R Work (Free-Float) is lower in flight than predicted. Accurate predictions of the metabolic cost of EVA are essential for planning and executing successful ISS EVAs. Overall, the current met rate prediction method is similar to actual in-flight values, slightly erring on the side of overestimation. Future work includes analysis of more historical in-flight EVA data to increase the power of the analysis, evaluating the NBL-ISS met rate conversion factor between NBL and ISS tasks, as well as exploring methods of substitution when crewmembers are missing prior task category data.

Lauren Cox↗
NASA NTRS2012

Advisory Algorithm for Scheduling Open Sectors, Operating Positions, and Workstations

Air traffic controller supervisors configure available sector, operating position, and work-station resources to safely and efficiently control air traffic in a region of airspace. In this paper, an algorithm for assisting supervisors with this task is described and demonstrated on two sample problem instances. The algorithm produces configuration schedule advisories that minimize a cost. The cost is a weighted sum of two competing costs: one penalizing mismatches between configurations and predicted air traffic demand and another penalizing the effort associated with changing configurations. The problem considered by the algorithm is a shortest path problem that is solved with a dynamic programming value iteration algorithm. The cost function contains numerous parameters. Default values for most of these are suggested based on descriptions of air traffic control procedures and subject-matter expert feedback. The parameter determining the relative importance of the two competing costs is tuned by comparing historical configurations with corresponding algorithm advisories. Two sample problem instances for which appropriate configuration advisories are obvious were designed to illustrate characteristics of the algorithm. Results demonstrate how the algorithm suggests advisories that appropriately utilize changes in airspace configurations and changes in the number of operating positions allocated to each open sector. The results also demonstrate how the advisories suggest appropriate times for configuration changes.

Bloem, Michael↗
NASA NTRS2022

A Robust Machine Learning Schema for Developing, Maintaining, and Disseminating Machine Learning Models

Recent advances in the development of machine learning (ML) algorithms have enabled the creation of predictive models that can improve decision making, decrease computational cost, and improve efficiency in a variety of fields. As an organization begins to develop and implement such models, the data used in the training, validation, and testing of ML models, the model parameters, and the use cases or limitations of the models must be properly stored to ensure models are both fully traceable and used correctly. In the context of predicting material behavior, advances in computationally intense, physics-based modeling of material behavior at various length scales and the emergence of Integrated Computational Materials Engineering (ICME) have driven the need for developing data-driven surrogate models of the physics-based simulation tools using ML techniques. Surrogate model development allows for accurate material behavior prediction at a fraction of the cost of its physics-based counterpart, allowing for multiscale simulations of real-world applications, further enabling the ability to design fit-for-purpose materials for a reasonable computational investment. However, training such models requires extensive data, and thus, effective data management is necessary to reach the full potential that ML can offer to material design and ICME. This paper proposes a generalized, robust schema that allows organizations to store both real (experimental) and virtual (simulation) data used to train ML models and the defining model parameters and architectures within the Granta MI Platform. The developed schema allows for various types of data inputs and outputs, including single point values, time-series data, and images that can be used in the prediction of material behavior, while following outlined best practices for effective data management. An effective schema for ML data and models can help prevent the recreation of virtual/real training data and surrogate models, help reduce the time to create new models similar to existing ones by offering a starting point in the hyperparameter determination stages, minimize resources devoted to verification and validation (V&V) and certification of models, and ensure that data and surrogate models are not misused due to full traceability of both the data and ML model. It also allows organizations access to models that have already been developed, such that they can be used in the design of new materials, enabling the overall goals of ICME.

Brandon L. Hearley↗
NASA NTRS1975

Demonstration of the feasibility of automated silicon solar cell fabrication

A study effort was undertaken to determine the process, steps and design requirements of an automated silicon solar cell production facility. Identification of the key process steps was made and a laboratory model was conceptually designed to demonstrate the feasibility of automating the silicon solar cell fabrication process. A detailed laboratory model was designed to demonstrate those functions most critical to the question of solar cell fabrication process automating feasibility. The study and conceptual design have established the technical feasibility of automating the solar cell manufacturing process to produce low cost solar cells with improved performance. Estimates predict an automated process throughput of 21,973 kilograms of silicon a year on a three shift 49-week basis, producing 4,747,000 hexagonal cells (38mm/side), a total of 3,373 kilowatts at an estimated manufacturing cost of $0.866 per cell or $1.22 per watt.

Taylor, W. E.↗
NASA NTRSDate not supplied

Predicting Fiber Failure of Plain Weave Fabric with Recursive Multiscale Micromechanics

Recent advances in the development of machine learning (ML) algorithms have enabled the creation of predictive models that can improve decision making, decrease computational cost, and improve efficiency in a variety of fields. As an organization begins to develop and implement such models, the data used in the training, validation, and testing of machine learning models, the model parameters, and the use cases or limitations of the models must be properly stored to ensure models are both fully traceable and used correctly. In the context of predicting material behavior, advances in computationally intense, physics-based, modeling of material behavior at various length scales, and the emergence of Integrated Computational Materials Engineering (ICME) have driven the need for developing data-driven surrogate models of the physics-based simulation tools using machine learning (ML) techniques. Surrogate model development allows for accurate material behavior prediction at a fraction of the cost of its physics-based counterpart, allowing for multiscale simulations of real-world applications, further enabling the ability to design fit-for-purpose materials for a reasonable computational investment. However, training such models requires extensive data, and thus effective data management is necessary to reach the full potential that ML can offer to material design and ICME. This paper proposes a generalized, robust schema that allows organizations to store both real (experimental) and virtual (simulation) data used to train machine learning models and the defining model parameters and architectures. The developed schema allows for various types of data inputs and outputs, including single point values, time-series data, and images that can be used in for various types of machine learning models while following outlined best practices for effective data management. An effective schema for machine learning data and models can help prevent the recreation of virtual/real training data and surrogate models, can help reduce the time to create new models similar to existing ones by offering a starting point in the hyperparameter determination stages, minimize resources devoted to verification and validation (V&V) and certification of models, and ensure that data and surrogate models are not misused due to full traceability of both the data and ML model. It also allows organizations access to models that have already been developed, such that they can be used in the design of new materials, enabling the overall goals of ICME.

Failure↗
NASA NTRS1976

Evaluation of a cost-effective loads approach

A shock spectra/impedance method for loads prediction is used to estimate member loads for the Viking Orbiter, a 7800-lb interplanetary spacecraft that has been designed using transient loads analysis techniques. The transient loads analysis approach leads to a lightweight structure but requires complex and costly analyses. To reduce complexity and cost a shock spectra/impedance method is currently being used to design the Mariner Jupiter Saturn spacecraft. This method has the advantage of using low-cost in-house loads analysis techniques and typically results in more conservative structural loads. The method is evaluated by comparing the increase in Viking member loads to the loads obtained by the transient loads analysis approach. An estimate of the weight penalty incurred by using this method is presented. The paper also compares the calculated flight loads from the transient loads analyses and the shock spectra/impedance method to measured flight data.

Garba, J. A.↗
NASA NTRS1976

Evaluation of a cost-effective loads approach

A shock spectra/impedance method for loads predictions is used to estimate member loads for the Viking Orbiter, a 7800-lb interplanetary spacecraft that has been designed using transient loads analysis techniques. The transient loads analysis approach leads to a lightweight structure but requires complex and costly analyses. To reduce complexity and cost, a shock spectra/impedance method is currently being used to design the Mariner Jupiter Saturn spacecraft. This method has the advantage of using low-cost in-house loads analysis techniques and typically results in more conservative structural loads. The method is evaluated by comparing the increase in Viking member loads to the loads obtained by the transient loads analysis approach. An estimate of the weight penalty incurred by using this method is presented. The paper also compares the calculated flight loads from the transient loads analyses and the shock spectra/impedance method to measured flight data.

Garba, J. A.↗
NASA NTRS2019

Scale-Resolving Simulations of Laminar-to-Turbulent Transition in Swept-Wing Flow

Aerodynamic shape optimization of swept Natural Laminar Flow (NLF) wing design plays an important role for the development of future energy-efficient commercial transport aircraft. Lack of predictive laminar-to-turbulent transition modeling capabilities is still limiting the extent to which design can rely on computational tools, while making costly wind tunnel and flight tests a necessity. Prediction of transition on practical 3D wing geometries using the e (sup N) method coupled with laminar boundary layer and linear stability codes or local statistical correlation CFD (Computational Fluid Dynamics) models such as the gamma - Re (sub theta) Langtry-Menter model have proven challenging, whereas transitional hybrid RANS-LES solvers have shown encouraging but still mitigated results.

Scale-resolving↗
NASA NTRS1978

Predicting Cost/Reliability/Maintainability of Advanced General Aviation Avionics Equipment

A methodology is provided for assisting NASA in estimating the cost, reliability, and maintenance (CRM) requirements for general avionics equipment operating in the 1980's. Practical problems of predicting these factors are examined. The usefulness and short comings of different approaches for modeling coast and reliability estimates are discussed together with special problems caused by the lack of historical data on the cost of maintaining general aviation avionics. Suggestions are offered on how NASA might proceed in assessing cost reliability CRM implications in the absence of reliable generalized predictive models.

Davis, M. R.↗
NASA NTRS1970

Nonlinear damping in structures

Experimental results prove the feasibility of substructure testing to measure local damping properties directly. Dynamic responses of a structure can be predicted quantitatively, and specimens are less costly and more easily tested with better controlled tests and environments.

Chang, C. S.↗
NASA NTRS1971

Advanced general aviation propeller study

Methods for predicting the performance, noise, weight, and cost of propellers for advanced general aviation aircraft of the 1980 time period were developed and computerized. This basic program was refined to incorporate a method of including the blade shape parameter, integrated design lift coefficient. This method and a reverse thrust computational procedure were included in the computer program. The weight equation was refined and also incorporated in the computer program. A User's Manual which includes a complete listing of this computer program with detailed instructions on its use has been written.

Worobel, R.↗