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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

A New Kind of Curing

A new curing method using automated tape placement (ATP) with electron beam (EB), or e-beam, produces a combination known as in situ e-beam curing. Through a Small Business Innovation Research (SBIR) contract from NASA's Marshall Space Flight Center, Science Research Laboratory, Inc., created the in situ e-beam curing technique, which uses a low-energy electron beam gun to cure various composite materials. One important benefit is the technique's utilization of room temperature curing, which lessens the chance of mismatching the thermal expansion coefficients of different materials. For instance, metals and composites will expand at different rates when heated, but the low-energy e-beam gun reduces the expansion differential. Using a low-energy gun also results in less x-ray shielding, significantly reduced capital costs, reduced facility space, and increased processing capabilities for larger parts. However, using a low-energy gun also means that each tape layer is treated individually because the gun can penetrate only one layer at a time. The e-beam gun emits lower energy x-rays, which are more easily shielded than those emitted by previous guns. The low-energy system is relatively portable due to its light weight and small size. The gun weighs about 70 pounds and can be easily mounted on a robotic arm or an ATP head.

Source record↗
NASA NTRS2008

Deconvoluting the Friction Stir Weld Process for Optimizing Welds

In the friction stir welding process, the rotating surfaces of the pin and shoulder contact the weld metal and force a rotational flow within the weld metal. Heat, generated by the metal deformation as well as frictional slippage with the contact surface, softens the metal and makes it easier to deform. As in any thermo-mechanical processing of metal, the flow conditions are critical to the quality of the weld. For example, extrusion of metal from under the shoulder of an excessively hot weld may relax local pressure and result in wormhole defects. The trace of the weld joint in the wake of the weld may vary geometrically depending upon the flow streamlines around the tool with some geometry more vulnerable to loss of strength from joint contamination than others. The material flow path around the tool cannot be seen in real time during the weld. By using analytical "tools" based upon the principles of mathematics and physics, a weld model can be created to compute features that can be observed. By comparing the computed observations with actual data, the weld model can be validated or adjusted to get better agreement. Inputs to the model to predict weld structures and properties include: hot working properties ofthe metal, pin tool geometry, travel rate, rotation and plunge force. Since metals record their prior hot working history, the hot working conditions imparted during FSW can be quantified by interpreting the final microstructure. Variations in texture and grain size result from variations in the strain accommodated at a given strain rate and temperature. Microstructural data from a variety of FSWs has been correlated with prior marker studies to contribute to our understanding of the FSW process. Once this stage is reached, the weld modeling process can save significant development costs by reducing costly trial-and-error approaches to obtaining quality welds.

Schneider, Judy↗
NASA NTRS2007

Automated Knowledge Discovery From Simulators

A computational method, SimLearn, has been devised to facilitate efficient knowledge discovery from simulators. Simulators are complex computer programs used in science and engineering to model diverse phenomena such as fluid flow, gravitational interactions, coupled mechanical systems, and nuclear, chemical, and biological processes. SimLearn uses active-learning techniques to efficiently address the "landscape characterization problem." In particular, SimLearn tries to determine which regions in "input space" lead to a given output from the simulator, where "input space" refers to an abstraction of all the variables going into the simulator, e.g., initial conditions, parameters, and interaction equations. Landscape characterization can be viewed as an attempt to invert the forward mapping of the simulator and recover the inputs that produce a particular output. Given that a single simulation run can take days or weeks to complete even on a large computing cluster, SimLearn attempts to reduce costs by reducing the number of simulations needed to effect discoveries. Unlike conventional data-mining methods that are applied to static predefined datasets, SimLearn involves an iterative process in which a most informative dataset is constructed dynamically by using the simulator as an oracle. On each iteration, the algorithm models the knowledge it has gained through previous simulation trials and then chooses which simulation trials to run next. Running these trials through the simulator produces new data in the form of input-output pairs. The overall process is embodied in an algorithm that combines support vector machines (SVMs) with active learning. SVMs use learning from examples (the examples are the input-output pairs generated by running the simulator) and a principle called maximum margin to derive predictors that generalize well to new inputs. In SimLearn, the SVM plays the role of modeling the knowledge that has been gained through previous simulation trials. Active learning is used to determine which new input points would be most informative if their output were known. The selected input points are run through the simulator to generate new information that can be used to refine the SVM. The process is then repeated. SimLearn carefully balances exploration (semi-randomly searching around the input space) versus exploitation (using the current state of knowledge to conduct a tightly focused search). During each iteration, SimLearn uses not one, but an ensemble of SVMs. Each SVM in the ensemble is characterized by different hyper-parameters that control various aspects of the learned predictor - for example, whether the predictor is constrained to be very smooth (nearby points in input space lead to similar output predictions) or whether the predictor is allowed to be "bumpy." The various SVMs will have different preferences about which input points they would like to run through the simulator next. SimLearn includes a formal mechanism for balancing the ensemble SVM preferences so that a single choice can be made for the next set of trials.

Burl, Michael↗
NASA NTRS2010

Ares I-X Ground Diagnostic Prototype

The automation of pre-launch diagnostics for launch vehicles offers three potential benefits: improving safety, reducing cost, and reducing launch delays. The Ares I-X Ground Diagnostic Prototype demonstrated anomaly detection, fault detection, fault isolation, and diagnostics for the Ares I-X first-stage Thrust Vector Control and for the associated ground hydraulics while the vehicle was in the Vehicle Assembly Building at Kennedy Space Center (KSC) and while it was on the launch pad. The prototype combines three existing tools. The first tool, TEAMS (Testability Engineering and Maintenance System), is a model-based tool from Qualtech Systems Inc. for fault isolation and diagnostics. The second tool, SHINE (Spacecraft Health Inference Engine), is a rule-based expert system that was developed at the NASA Jet Propulsion Laboratory. We developed SHINE rules for fault detection and mode identification, and used the outputs of SHINE as inputs to TEAMS. The third tool, IMS (Inductive Monitoring System), is an anomaly detection tool that was developed at NASA Ames Research Center. The three tools were integrated and deployed to KSC, where they were interfaced with live data. This paper describes how the prototype performed during the period of time before the launch, including accuracy and computer resource usage. The paper concludes with some of the lessons that we learned from the experience of developing and deploying the prototype.

Schwabacher, Mark A.↗
NASA NTRS2003

Autonomous Mission Manager for Rendezvous, Inspection and Mating

To meet cost and safety objectives, space missions that involve proximity operations between two vehicles require a high level of autonomy to successfully complete their missions. The need for autonomy is primarily driven by the need to conduct complex operations outside of communication windows, and the communication time delays inherent in space missions. Autonomy also supports the goals of both NASA and the DOD to make space operations more routine, and lower operational costs by reducing the requirement for ground personnel. NASA and the DoD have several programs underway that require a much higher level of autonomy for space vehicles. NASA's Space Launch Initiative (SLI) program has ambitious goals of reducing costs by a factor or 10 and improving safety by a factor of 100. DARPA has recently begun its Orbital Express to demonstrate key technologies to make satellite servicing routine. The Air Force's XSS-ll program is developing a protoflight demonstration of an autonomous satellite inspector. A common element in space operations for many NASA and DOD missions is the ability to rendezvous, inspect anclJor dock with another spacecraft. For DARPA, this is required to service or refuel military satellites. For the Air Force, this is required to inspect un-cooperative resident space objects. For NASA, this is needed to meet the primary SLI design reference mission of International Space Station re-supply. A common aspect for each of these programs is an Autonomous Mission Manager that provides highly autonomous planning, execution and monitoring of the rendezvous, inspection and docking operations. This paper provides an overview of the Autonomous Mission Manager (AMM) design being incorporated into many of these technology programs. This AMM provides a highly scalable level of autonomous operations, ranging from automatic execution of ground-derived plans to highly autonomous onboard planning to meet ground developed mission goals. The AMM provides the capability to automatically execute the plans and monitor the system performance. In the event of system dispersions or failures the AMM can modify plans or abort to assure overall system safety. This paper describes the design and functionality of Draper's AMM framework, presents concept of operations associated with the use of the AMM, and outlines the relevant features of the flight demonstrations.

Zimpfer, Douglas J.↗
NASA NTRS2010

Ares I-X Ground Diagnostic Prototype

Automating prelaunch diagnostics for launch vehicles offers three potential benefits. First, it potentially improves safety by detecting faults that might otherwise have been missed so that they can be corrected before launch. Second, it potentially reduces launch delays by more quickly diagnosing the cause of anomalies that occur during prelaunch processing. Reducing launch delays will be critical to the success of NASA's planned future missions that require in-orbit rendezvous. Third, it potentially reduces costs by reducing both launch delays and the number of people needed to monitor the prelaunch process. NASA is currently developing the Ares I launch vehicle to bring the Orion capsule and its crew of four astronauts to low-earth orbit on their way to the moon. Ares I-X will be the first unmanned test flight of Ares I. It is scheduled to launch on October 27, 2009. The Ares I-X Ground Diagnostic Prototype is a prototype ground diagnostic system that will provide anomaly detection, fault detection, fault isolation, and diagnostics for the Ares I-X first-stage thrust vector control (TVC) and for the associated ground hydraulics while it is in the Vehicle Assembly Building (VAB) at John F. Kennedy Space Center (KSC) and on the launch pad. It will serve as a prototype for a future operational ground diagnostic system for Ares I. The prototype combines three existing diagnostic tools. The first tool, TEAMS (Testability Engineering and Maintenance System), is a model-based tool that is commercially produced by Qualtech Systems, Inc. It uses a qualitative model of failure propagation to perform fault isolation and diagnostics. We adapted an existing TEAMS model of the TVC to use for diagnostics and developed a TEAMS model of the ground hydraulics. The second tool, Spacecraft Health Inference Engine (SHINE), is a rule-based expert system developed at the NASA Jet Propulsion Laboratory. We developed SHINE rules for fault detection and mode identification. The prototype uses the outputs of SHINE as inputs to TEAMS. The third tool, the Inductive Monitoring System (IMS), is an anomaly detection tool developed at NASA Ames Research Center and is currently used to monitor the International Space Station Control Moment Gyroscopes. IMS automatically "learns" a model of historical nominal data in the form of a set of clusters and signals an alarm when new data fails to match this model. IMS offers the potential to detect faults that have not been modeled. The three tools have been integrated and deployed to Hangar AE at KSC where they interface with live data from the Ares I-X vehicle and from the ground hydraulics. The outputs of the tools are displayed on a console in Hangar AE, one of the locations from which the Ares I-X launch will be monitored. The full paper will describe how the prototype performed before the launch. It will include an analysis of the prototype's accuracy, including false-positive rates, false-negative rates, and receiver operating characteristics (ROC) curves. It will also include a description of the prototype's computational requirements, including CPU usage, main memory usage, and disk usage. If the prototype detects any faults during the prelaunch period then the paper will include a description of those faults. Similarly, if the prototype has any false alarms then the paper will describe them and will attempt to explain their causes.

Schwabacher, Mark↗
NASA NTRSDate not supplied

TPSAS-NF1676L-18391-DND

Vehicle weight is a primary driver for most NASA missions. Reducing vehicle weight can: - Expand mission capability - Reduce launch costs - Reduce fuel consumption - Systems analysis shows that reducing materials mass by 20% leads to a 30% reduction in launch vehicle gross weight - Same study indicates a 50% reduction in materials mass reduces launch vehicle gross weight by >60%, enables potential single stage to orbit designs - Additional multifunctionality: thermal, radiation protection, sensing capabilities, no corrosion Potential Impact: Produce advanced lightweight structural BNNT composites with higher thermal stability, no corrosion, high toughness, sensing/actuation, and radiation shielding effectiveness.

Cheol Park↗
NASA NTRSDate not supplied

Vision 2030 Aircraft Propulsion Grand Challenge Problem: Full-engine CFD Simulations with High Geometric Fidelity and Physics Accuracy

In 2014 NASA published the outcome of the 2030 CFD Vision study: “CFD Vision 2030: A path to Revolutionary Computational Aerosciences” (Slotnick et al., 2014). The study provided a comprehensive review of the state of the art of CFD in 2014 for aerospace applications including, but not limited to, numerical algorithms, physics models, MDAO and HPC hardware. The study also proposed four conceptual ideas of Grand Challenge problems that would benefit from advances outlined in the roadmap including “off-design turbofan engine transient simulation”. The proposed challenges served as a starting point for more detailed problem descriptions that would benefit from advances in simulation. The objective of this paper is to build upon the NASA 2030 CFD Vision study and provide a detailed overview of what needs to take place to enable accurate and efficient simulation of flow through an aircraft engine at off-design condition for transient operation . Execution of the proposed roadmap would significantly advance aircraft engine development by reducing program cost, reducing program development timelines and enabling design objectives associated with Specific Fuel Consumption (SFC), noise, weight and durability.

compressor↗
NASA NTRS1992

Elements of designing for cost

During recent history in the United States, government systems development has been performance driven. As a result, systems within a class have experienced exponentially increasing cost over time in fixed year dollars. Moreover, little emphasis has been placed on reducing cost. This paper defines designing for cost and presents several tools which, if used in the engineering process, offer the promise of reducing cost. Although other potential tools exist for designing for cost, this paper focuses on rules of thumb, quality function deployment, Taguchi methods, concurrent engineering, and activity-based costing. Each of these tools has been demonstrated to reduce cost if used within the engineering process.

Dean, Edwin B.↗
NASA NTRS1992

Elements of Designing for Cost

During recent history in the United States, government systems development has been performance driven. As a result, systems within a class have experienced exponentially increasing cost over time in fixed year dollars. Moreover, little emphasis has been placed on reducing cost. This paper defines designing for cost and presents several tools which, if used in the engineering process, offer the promise of reducing cost. Although other potential tools exist for designing for cost, this paper focuses on rules of thumb, quality function deployment, Taguchi methods, concurrent engineering, and activity based costing. Each of these tools has been demonstrated to reduce cost if used within the engineering process.

Dean, Edwin B.↗
NASA NTRS1993

Adaptive function allocation reduces performance costs of static automation

Adaptive automation offers the option of flexible function allocation between the pilot and on-board computer systems. One of the important claims for the superiority of adaptive over static automation is that such systems do not suffer from some of the drawbacks associated with conventional function allocation. Several experiments designed to test this claim are reported in this article. The efficacy of adaptive function allocation was examined using a laboratory flight-simulation task involving multiple functions of tracking, fuel-management, and systems monitoring. The results show that monitoring inefficiency represents one of the performance costs of static automation. Adaptive function allocation can reduce the performance cost associated with long-term static automation.

Parasuraman, Raja↗
DOE OSTI2025

Technology & Design Innovations to Maximize the Reduction Effect on DCFC Unit Cost Economics (Max‐REDUCE)

With the high cost and reliability issues of DCFC infrastructure the project specifically addressed the needs of innovating on the AC to DC power conversion. We proved the integration of a new power module into existing charger units, and that theoretical educational work on single stage energy conversion is commercially viable, and a reduced cost compared to existing methods. Our A sample shown 3 PH 480VAC 60hz to 350VDC 8.5kW power transfer, and our software and simulation proved efficiency greater than 97% from 20kW to > 60kW, over the DC output voltage range 200 – 1200V. The project was stopped before we could implement B sample and execute full power testing, validation and integration into a demonstration charger (budget period 3).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Machine learning reduces soft costs for residential solar photovoltaics

Further deployment of rooftop solar photovoltaics (PV) hinges on the reduction of soft (non-hardware) costs—now larger and more resistant to reductions than hardware costs. The largest portion of these soft costs is the expenses solar companies incur to acquire new customers. In this study, we demonstrate the value of a shift from significance-based methodologies to prediction-oriented models to better identify PV adopters and reduce soft costs. We employ machine learning to predict PV adopters and non-adopters, and compare its prediction performance with logistic regression, the dominant significance-based method in technology adoption studies. Our results show that machine learning substantially enhances adoption prediction performance: The true positive rate of predicting adopters increased from 66 to 87%, and the true negative rate of predicting non-adopters increased from 75 to 88%. We attribute the enhanced performance to complex variable interactions and nonlinear effects incorporated by machine learning. With more accurate predictions, machine learning is able to reduce customer acquisition costs by 15% ($0.07/Watt) and identify new market opportunities for solar companies to expand and diversify their customer bases. Our research methods and findings provide broader implications for the adoption of similar clean energy technologies and related policy challenges such as market growth and energy inequality.

14 SOLAR ENERGY↗
NASA NTRS1999

Reducing Mission Costs by Leveraging Previous Investments in Space

The Rapid Spacecraft Development Office (RSDO) at NASA's Goddard Space Flight Center has been charged with the responsibility to reduce mission cost by allowing access to previous developments on government and commercial space missions. RSDO accomplishes this responsibility by implementing two revolutionary contract vehicles, the Rapid Spacecraft Acquisition (RSA) and Quick Ride. This paper will describe the concept behind these contracts, the current capabilities available to missions, analysis of pricing trends to date using the RSDO processes, and future plans to increase flexibility and capabilities available to mission planners.

Miller, Ron↗
DOE OSTI2024

Reducing the cost of home energy upgrades in the US: An industry survey

Decarbonizing the US residential building stock requires a substantial acceleration in home energy upgrades. Numerous barriers exist to accelerating adoption of efficient and electric building technologies, but foremost among these is high upfront costs. This study uses an industry survey delivered to a sample of home energy professionals to examine promising cost reduction strategies across a range of project types, including HVAC, water heating, and envelope/insulation projects. The survey included quantitative and qualitative questions to collect evidence on the estimated cost reduction potential of these strategies and their likelihood of use in the construction industry. The 167 survey respondents included contractors, energy consultants, architects, manufacturers, and others with experience in delivering energy upgrades in single-family and multifamily buildings in the US. Results show that significant cost reductions are achievable by minimizing additional infrastructure costs (such as replacing electric panels), streamlining project planning/management, and deploying innovations that simplify installation. We find that for a typical deep retrofit project, including heat pumps for space and water heating in addition to envelope upgrades, the strategies could result in a total installed cost reduction of nearly 50%, dramatically improving the customer economics of such a project. This research makes a novel contribution to the literature on strategies to reduce the costs of residential retrofits. We discuss how our study's insights on the highest-value cost reduction strategies for home energy upgrades can further accelerate their uptake in the US housing stock.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1998

Advanced Fuels Can Reduce the Cost of Getting Into Space

Rocket propellant and propulsion technology improvements can reduce the development time and operational costs of new space vehicle programs, and advanced propellant technologies can make space vehicles safer and easier to operate, and can improve their performance. Five major areas have been identified for fruitful research: monopropellants, alternative hydrocarbons, gelled hydrogen, metallized gelled propellants, and high-energy-density propellants. During the development of the NASA Advanced Space Transportation Plan, these technologies were identified as those most likely to be effective for new NASA vehicles. Several NASA research programs had fostered work in fuels under the topic Fuels and Space Propellants for Reusable Launch Vehicles in 1996 to 1997. One component of this topic was to promote the development and commercialization of monopropellant rocket fuels, hypersonic fuels, and high-energy-density propellants. This research resulted in the teaming of small business with large industries, universities, and Government laboratories. This work is ongoing with seven contractors. The commercial products from these contracts will bolster advanced propellant research. Work also is continuing under other programs, which were recently realigned under the "Three Pillars" of NASA: Global Civil Aviation, Revolutionary Technology Leaps, and Access to Space. One of the five areas is described below, and its applications and effect on future missions is discussed. This work is being conducted at the NASA Lewis Research Center with the assistance of the NASA Marshall Space Flight Center. The regenerative cooling of spacecraft engines and other components can improve overall vehicle performance. Endothermic fuels can absorb energy from an engine nozzle and chamber and help to vaporize high-density fuel before it enters the combustion chamber. For supersonic and hypersonic aircraft, endothermic fuels can absorb the high heat fluxes created on the wing leading edges and other aerodynamically heated components. Dual-fuel options are also possible, where endothermic hydrocarbon fuels are used for the lower speed portions of flight below Mach 8, and hydrogen fuel is used for the final acceleration to the upper stage separation velocity.

Palaszewski, Bryan A.↗
DOE OSTI2024

Recovery of Oxpure 612C-50 Coconut Carbon Particles Using Bump Arrays

Cyanide is used to leach gold from crushed ore (solid matrix) into a gold cyanide solution. The gold is extracted from the cyanide solution by adsorption onto activated carbon. The gold extraction process occurs when the activated coconut carbon is placed into tanks that contain the gold cyanide solution either in a batch process or into a continuous flow circuit. The coconut carbon is then removed from the solution for gold recovery. The use of the mesofluidic separation system (a deterministic lateral displacement system) can significantly reduce costs and waste generated from the process of removing the coconut carbon from the solution. In the coconut carbon recovery process used at many gold mines in Nevada, the gold is attached to carbon particles that are still in the cyanide liquor. The mesofluidic system can rapidly remove the gold bearing carbon particles from the cyanide liquor quickly and with no operating costs. The benefits include: • Reduce operational costs related to filtration and hydro-cyclones • Reduced acid usage for the elution gold stripping phase as only 25% of the fluids will follow the carbon particles to the final express lane when two mesofluidic systems are used in series This alternative particle removal techniques would be advantageous. A promising technique for removing larger particles from slurries is mesofluidic separation, similar to deterministic lateral displacement arrays or “bump” arrays [1] but operates at much larger flow rates. As described by Pease, et al. [2], “Bump arrays in deterministic lateral displacement devices separate large particles from small particles using arrays of staggered posts. Large particles, defined as those with radii larger than the distance between the edge of a post and the stagnation streamline from the next downstream post, must bump toward one side of the device, whereas particles smaller than this distance slalom from entrance to exit without net lateral displacement.” Unlike filters or sieves, the posts in the arrays that cause separation do not block or occlude particle flow but work because particles go around the posts. Unlike hydrocyclones separation, separation is not driven by particle density, because gravitational forces are unimportant to mesofluidic separation. Burns, et al., and Pease, et al., have shown that particles may be separated from complex suspensions, under turbulent flow conditions, and at industrially important flow rates [3-5]. They have also recently shown that mesofluidic devices may be arranged in series to increase separation performance [6]. In this paper, we evaluate the mesofluidic system for the separation of commercial OxPure GR 612 Charred Coconut shell particles as a proof of principle test for the rapid separation using the 1500 micron cut mesofluidic separator. We first describe the experimental system and conditions. We then present the experimental results. [1] Huang, L.R., E.C. Cox, R.H. Austin, J.C. Sturm. 2004. Continuous particle separation through deterministic lateral displacement. Science, 304, 987–990. https://doi.org/10.1126/science.1094567. [2] Pease L.F., J.A. Bamberger, C.A. Burns, and M.J. Minette. 2021. Large Particle Separation from Non-Newtonian Slurries using Bump Arrays. In Proceedings of the ASME 2021 Fluids Engineering Division Summer Meeting FEDSM2021-65904, V003T08A023. New York, New York: ASME. doi:10.1115/FEDSM2021-65904 [3] Burns C.A., T.G. Veldman, J. Serkowski, R.C. Daniel, X.-Y. Yu, M.J. Minette, L.F. Pease. 2021. Mesofluidic separation versus dead-end filtration. Separation and Purification Technology, 254, 117256. https://doi.org/10.1016/j.seppur.2020.117256. [4] Pease L.F., J.E. Serkowski, T.G. Veldman, J. Williams, X.-Y. Yu, M.J. Minette, J.A. Bamberger, C.A. Burns. 2021. Can Bump Arrays Separate Particles from Turbulent Flows?. In Proceedings of the ASME 2021 Fluids Engineering Division Summer Meeting FEDSM2021-67696, V003T08A024. New York, New York: ASME. doi:10.11

mesofluidic separation, slurry, bump array↗