Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Generative Design”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

An Integrated Vehicle Modeling Environment

This paper describes an Integrated Vehicle Modeling Environment for estimating aircraft geometric, inertial, and aerodynamic characteristics, and for interfacing with a high fidelity, workstation based flight simulation architecture. The goals in developing this environment are to aid in the design of next generation intelligent fight control technologies, conduct research in advanced vehicle interface concepts for autonomous and semi-autonomous applications, and provide a value-added capability to the conceptual design and aircraft synthesis process. Results are presented for three aircraft by comparing estimates generated by the Integrated Vehicle Modeling Environment with known characteristics of each vehicle under consideration. The three aircraft are a modified F-15 with moveable canards attached to the airframe, a mid-sized, twin-engine commercial transport concept, and a small, single-engine, uninhabited aerial vehicle. Estimated physical properties and dynamic characteristics are correlated with those known for each aircraft over a large portion of the flight envelope of interest. These results represent the completion of a critical step toward meeting the stated goals for developing this modeling environment.

Totah, Joseph J.↗
NASA NTRSDate not supplied

Particle Loading Tests on HEPA Flat Sheet Media at Sub-Ambient Pressures Using a Lunar Dust Simulant

When humans return to the moon under the NASA Artemis program, their activities on the lunar surface will inevitably lead to the intrusion of some level of lunar dust into the lander cabin. Therein the crew would be exposed to the potential hazards of lunar dust and the possibility of subsequent transfer into orbiting segments after docking. The spacecraft’s cabin filtration system will need to be effective at removing the airborne lunar dust to properly purify the breathable cabin air and minimize the spreading of the dust throughout the vehicle and orbital segments through the mission duration. The fine nature of the lunar dust will require high efficiency filtration, such as HEPA. A series of tests were performed in a specially designed recirculating sealed flow loop, for testing filter media and filter elements at the NASA Glenn Research Center. The flow loop was used to assess the performance and capacity of flat sheet filter media at representative cabin pressures using JSC-1AF lunar dust simulant and at high rates of particle loading. The pressure drop across the filter media was measured as a function of accumulated particle mass load at ambient pressure and at two sub-ambient pressures, 0.0703MPa and 0.0565MPa, and at a media velocity that was scaled relative to its pleated configuration. The challenge particle flows were generated by a custom designed particle generator that introduces dispersed particles of the lunar simulant at high concentrations. An optical particle counting instrument provided filter efficiency measurements within the sealed environment. The pressure drop was found to increase linearly with the amount of dust load on the media, for all test conditions, while the starting pressure drop was found to be lower at the lowest sub-ambient pressure case. High filter efficiency was maintained after high particle loads on the media.

Sub-ambient↗
NASA NTRSDate not supplied

Particle Loading Tests on HEPA Flat Sheet Media at Sub-Ambient Pressures Using a Lunar Dust Simulant

When humans return to the moon under the NASA Artemis program, their activities on the lunar surface will inevitably lead to the intrusion of some level of lunar dust into the lander cabin. Therein the crew would be exposed to the potential hazards of lunar dust and the possibility of subsequent transfer into orbiting segments after docking. The spacecraft’s cabin filtration system will need to be effective at removing the airborne lunar dust to properly purify the breathable cabin air and minimize the spreading of the dust throughout the vehicle and orbital segments through the mission duration. The fine nature of the lunar dust will require high efficiency filtration, such as HEPA. A series of tests were performed in a specially designed recirculating sealed flow loop, for testing filter media and filter elements at the NASA Glenn Research Center. The flow loop was used to assess the performance and capacity of flat sheet filter media at representative cabin pressures using JSC-1AF lunar he filter media was measured as a function of accumulated particle mdust simulant and at high rates of particle loading. The pressure drop across tass load at ambient pressure and at two sub-ambient pressures, 0.0703MPa and 0.0565MPa, and at a media velocity that was scaled relative to its pleated configuration. The challenge particle flows were generated by a custom designed particle generator that introduces dispersed particles of the lunar simulant at high concentrations. An optical particle counting instrument provided filter efficiency measurements within the sealed environment. The pressure drop was found to increase linearly with the amount of dust load on the media, for all test conditions, while the starting pressure drop was found to be lower at the lowest sub-ambient pressure case. High filter efficiency was maintained after high particle loads on the media

Sub-ambient↗
NASA NTRS1984

A Summary Description of a Computer Program Concept for the Design and Simulation of Solar Pond Electric Power Generation Systems

A solar pond electric power generation subsystem, an electric power transformer and switch yard, a large solar pond, a water treatment plant, and numerous storage and evaporation ponds. Because a solar pond stores thermal energy over a long period of time, plant operation at any point in time is dependent upon past operation and future perceived generation plans. This time or past history factor introduces a new dimension in the design process. The design optimization of a plant must go beyond examination of operational state points and consider the seasonal variations in solar, solar pond energy storage, and desired plant annual duty-cycle profile. Models or design tools will be required to optimize a plant design. These models should be developed in order to include a proper but not excessive level of detail. The model should be targeted to a specific objective and not conceived as a do everything analysis tool, i.e., system design and not gradient-zone stability.

Source record↗
DOE OSTI2025

Multi-objective automatic discovery of optimized metamaterials for varying velocity impact protection

Mechanical metamaterials have demonstrated exceptional impact performance while remaining lightweight. Impact resistance has traditionally been investigated using quasi-static simulations, often with the assumption that performance will translate to high-velocity impact scenarios. However, critical crash protection parameters—such as peak stress and absorbed energy—are highly sensitive to impact velocity, leading to inconsistent performance under dynamic loading. To address this, we introduce a strain-rate-aware, active deep learning framework that enables multi-objective optimization of impact protection metrics across a wide range of impact velocities. Our framework captures the strain-rate sensitivity of architected lattices by learning to control spatial gradation in cellular metamaterials, resulting in over 200 % enhancement in impact protection relative to state-of-the-art designs such as Voronoi and re-entrant lattices. We demonstrate its practical utility by designing next-generation lattice structures for automotive bumper systems that satisfy multiple, velocity-specific safety criteria—capabilities beyond those of conventional designs. More than just a predictive tool, this framework marks the first step towards enabling adaptable impact-resistant structures across dynamic regimes.

Deep learning↗
NASA NTRS1974

Application of optimality criteria in structural synthesis

The rational use of optimality criteria was investigated for a class of structural synthesis problems where materials, configuration and applied load conditions are specified, and the minimum weight design is to be determined. The potential of hybrid methods of structural optimization for dealing with relatively large design problems involving practical complexity was explored. The reduced basis concept in design space was used to decrease the number of generalized design variables dealt with by the mathematical programming algorithm. Optimality criteria methods for obtaining design vectors associated with displacement, system buckling and natural frequency constraints are presented. A stress ratio method was used to generate a basis design vector representing the stress constraints. The finite element displacement method was used as the basic structural analysis tool. Results for several examples of truss systems subject to stress, displacement and minimum size constraints are presented. An assessment of these results indicates the effectiveness of the hybrid method developed.

Terai, K.↗
NASA NTRS1988

Breadboard RL10-2B low-thrust operating mode (second iteration) test report

Cryogenic rocket engines requiring a cooling process to thermally condition the engine to operating temperature can be made more efficient if cooling propellants can be burned. Tank head idle and pumped idle modes can be used to burn propellants employed for cooling, thereby providing useful thrust. Such idle modes required the use of a heat exchanger to vaporize oxygen prior to injection into the combustion chamber. During December 1988, Pratt and Whitney conducted a series of engine hot firing demonstrating the operation of two new, previously untested oxidizer heat exchanger designs. The program was a second iteration of previous low thrust testing conducted in 1984, during which a first-generation heat exchanger design was used. Although operation was demonstrated at tank head idle and pumped idle, the engine experienced instability when propellants could not be supplied to the heat exchanger at design conditions.

Kanic, Paul G.↗
DOE OSTI2024

Influence of Joule Heating on the Stability of High Temperature Irradiation-resistant Thermocouples

Development of in-core instrumentation is driven by the pursuit of safer, more economic energy production from the perspective of both existing nuclear reactors and Generation IV reactor designs. Idaho National Laboratory has developed high-temperature irradiation-resistant thermocouples (HTIR-TCs) for temperature sensing inside Generation IV nuclear reactors. These thermocouples are composed of phosphorus-doped niobium (Nb-P) and lanthana-doped molybdenum (Mo-LaO) thermoelements, an alumina (Al2O3) insulation, and a niobium sheath. HTIR-TCs require an initial heat treatment exceeding the maximum service temperature to stabilize the generated electromotive force (EMF) signal. The mechanism behind the stabilization of the HTIR-TCs through traditional heat treatment methods is understood; however, the traditional heat treatment method is expensive, time consuming, and results in a heterogeneous microstructure. Therefore, we investigated a rapid method for stabilization and microstructure homogeneity, through Joule heating. This work evaluates the impact of Joule heating on the thermoelements’ microstructures, chemical stability, and mechanical properties so as to determine the mechanisms by which stabilization of the EMF signal occurs. Accordingly, during the Joule heat treatment, a secondary Nb3P phase coarsened along the length of the Nb-P thermoelement, along with the formation of an interaction region at the Al2O3/niobium interface. The interaction between the alumina insulation and the Nb-P thermoelement was also observed within the Mo-LaO thermoelement. Joule heating induced stability within the generated HTIR-TC EMF signal via the formation of secondary phases within the Nb-P and the interaction between the alumina insulation and the thermoelements.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2025

Fuel performance analysis of fully-resolved TRISO compact

The TRi-structural ISOtropic (TRISO) fuel multilayered coating structure offers multiple barriers to fission product release, enhancing safety and performance. The heterogeneous nature of TRISO fuel compacts, comprising thousands of randomly distributed coated fuel particles embedded in a graphite matrix, creates intricate stress fields and thermal gradients that cannot be accurately modeled using simplified one-dimensional or homogenized approaches. Consequently, three-dimensional modeling enables the prediction of fuel compact dimensional changes, internal pressure buildup, and fission product transport pathways under diverse irradiation and thermal conditions. This capability facilitates detailed analysis of particle-to-particle interactions, matrix cracking mechanisms, and the statistical distribution of coating failures, which directly impact fuel performance and safety margins. This capability is particularly critical for advanced reactors, such as high-temperature gas-cooled reactors and other Generation IV reactor designs where TRISO fuel operates at elevated temperatures and burn-up levels. This work introduces a novel method to generate an optimized packing of TRISO compacts and a complete 3D mesh with random distribution of TRISO particles, which are discretized into each coating component layer.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2013

Toward the Next Generation of Air Quality Monitoring Indicators

This paper introduces an initiative to bridge the state of scientific knowledge on air pollution with the needs of policymakers and stakeholders to design the "next generation" of air quality indicators. As a first step this initiative assesses current monitoring and modeling associated with a number of important pollutants with an eye toward identifying knowledge gaps and scientific needs that are a barrier to reducing air pollution impacts on human and ecosystem health across the globe. Four outdoor air pollutants were considered e particulate matter, ozone, mercury, and Persistent Organic Pollutants (POPs) e because of their clear adverse impacts on human and ecosystem health and because of the availability of baseline data for assessment for each. While other papers appearing in this issue will address each pollutant separately, this paper serves as a summary of the initiative and presents recommendations for needed investments to provide improved measurement, monitoring, and modeling data for policyrelevant indicators. The ultimate goal of this effort is to enable enhanced public policy responses to air pollution by linking improved data and measurement methods to decision-making through the development of indicators that can allow policymakers to better understand the impacts of air pollution and, along with source attribution based on modeling and measurements, facilitate improved policies to solve it. The development of indicators represents a crucial next step in this process.

Particulate matter↗
DOE OSTI2024

LENS: Learning Enabled Network Synthesis

RTRC and UMD have developed novel machine learning based methods under the ARPA-E DIFFERENTIATE program for rapid acceleration of hypothesis generation in complex architecture design spaces involving both discrete choices of component inclusion and interconnection and continuous parametric decisions. The project named Learning Enabled Network Synthesis (LENS) further demonstrated the developed methods on challenging electrical power converter design problems by identifying the most suitable circuit topologies and simultaneously selecting the most appropriate components to achieve optimized design of power converter with improved performances. We demonstrated that LENS could enable exploration of very large design space of circuit topologies and components by addressing the limitations of conventional design process in non-linear, high switching speed, multi-dimensional power converter design and optimization. The key innovation developed in LENS is the seamless integration of statistical learning and logical reasoning techniques and building on the individual strengths of these techniques for rapid hypothesis discovery. The main component of LENS comprises of: 1) Graph Reasoning Engine (GRE) to enforce composition rules that rapidly reject all discrete architectures that are composed incorrectly and generates an adaptive database of feasible designs which can be used by ML modules, 2) Graph Generative Learning module which is a deep neural network based generative model for graph architectures which can enable design space exploration beyond the dataset generated by the GRE, 3) Graph Reduced Order Model (ROM) for graph domains for accelerating computation of output metrics, and 4) Active learning and Rule Discovery module for sample efficient learning and extracting logical rules from the learned ML models which will be integrated in the GRE to enhance the filtering effectiveness. LENS approach can be applied to any design domains where designs can be represented as multi-attribute graphs. The LENS team integrated the various technical innovations listed above into an optimization pipeline and exercised the optimization pipeline on the converter design problem. The LENS project demonstrated that the developed AI/ML technologies can be used to generate novel converter circuits >45x faster than experts on chosen use-cases. This can enable faster design space exploration and identification of new designs which are not considered by experts due to the increasing design space complexity. This has significant potential impact on the public and energy needs of the country. It is currently estimated that 30% of all electrical powers generated passes through power converters. The future estimate is that 80% of all power generated would be passing through converters. LENS fills a critical gap in this space since by accelerating the design process the designers would be able to generate more efficient converters which can lead to significant energy savings for the country.

42 ENGINEERING↗
DOE OSTI2022

Design of a PIP-II Era Mu2e Experiment

We propose a design of an upgraded Mu2e experiment for the future Fermilab PIP-II era based on the muon collider front end. The consensus is that such an upgrade should provide a factor of 10 increase in the rate of stopping muons in the experimental target. The current Mu2e design is optimized for 8 kW of protons at 8 GeV. The PIP-II upgrade project is a 250-meter-long CW linac capable of accelerating a 2-mA proton beam to a kinetic energy of 800 MeV (total power 1.6 MW). This would significantly improve the Fermilab proton source to enable next-generation intensity frontier experiments. But using this 800 MeV beam poses challenges to the Mu2E experiment. Bright muon beams generated from sources designed for muon collider and neutrino factory facilities have been shown to generate two orders of magnitude more muons per proton than the current Mu2e production target and solenoid. In contrast to the current Mu2e, the muon collider design has forward-production of muons from the target.

43 PARTICLE ACCELERATORS↗
NASA NTRS1991

High speed civil transport

This report discusses the design and marketability of a next generation supersonic transport. Apogee Aeronautics Corporation has designated its High Speed Civil Transport (HSCT): Supercruiser HS-8. Since the beginning of the Concorde era, the general consensus has been that the proper time for the introduction of a next generation Supersonic Transport (SST) would depend upon the technical advances made in the areas of propulsion (reduction in emissions) and material composites (stronger, lighter materials). It is believed by many in the aerospace industry that these beforementioned technical advances lie on the horizon. With this being the case, this is the proper time to begin the design phase for the next generation HSCT. The design objective for a HSCT was to develop an aircraft that would be capable of transporting at least 250 passengers with baggage at a distance of 5500 nmi. The supersonic Mach number is currently unspecified. In addition, the design had to be marketable, cost effective, and certifiable. To achieve this goal, technical advances in the current SST's must be made, especially in the areas of aerodynamics and propulsion. As a result of these required aerodynamic advances, several different supersonic design concepts were reviewed.

Source record↗
DOE OSTI2023

Approaches for Synthesis and Deployment of Controller Models on Automated Vehicles for Car-following in Mixed Autonomy

This paper describes the software design patterns and vehicle interfaces that were employed to transition vehicle controllers from simulation environments to open-road field experiments. The approach relies on a life cycle that utilizes model-based design and code generation, along with agile software development, and both software and hardware-in-the-loop testing, with additional safety margins. Autonomous designs should consider the dynamics of mixed autonomy in traffic to safely operate among humans. The software that provides a vehicle’s behavior intelligence is often developed through simulation, which may have a mismatch between dynamics, or as a result of a reinforcement learning workflow, which may be a black box with challenges to analyze. In each of these cases, it is important to have research interfaces that provide strongly typed data streams accessible to researchers who are not software experts while continuing to satisfy safety and liveness constraints. This paper describes how we design the hardware platform interfaces and software design process for a mixed autonomy traffic experiment with a leader-follower scenario. Controller synthesis for these vehicles requires clearly articulated vehicle interfaces and software design patterns for successful onboard deployment. Testing strategies for such controllers are also described before algorithms are transitioned to full-scale field experiments with safety operators for the vehicles. Testing strategies include software-in-the-loop simulation testing, hardware-in-the-loop simulation, ghost-car testing, and read-only testing in live traffic. With our approach, we were not only able to validate our controller synthesized in scripts and simulation, but also able to scale deployment to multiple vehicles.

Bhadani, Rahul↗
NASA NTRS1991

Combined control-structural optimization

An approach to combined control-structural optimization aimed at enhancing early design trade-offs is outlined and illustrated by numerical examples. The approach employs a homotopic strategy and is capable of generating families of designs that can be used in early trade studies. Analytical results are obtained for classes of structure/control objectives with LQG and LQR costs. For these, it is demonstrated that global optima can be computed for small values of the homotopy parameter.

Milman, M.↗
NASA NTRS2000

Towards Evolving Electronic Circuits for Autonomous Space Applications

The relatively new field of Evolvable Hardware studies how simulated evolution can reconfigure, adapt, and design hardware structures in an automated manner. Space applications, especially those requiring autonomy, are potential beneficiaries of evolvable hardware. For example, robotic drilling from a mobile platform requires high-bandwidth controller circuits that are difficult to design. In this paper, we present automated design techniques based on evolutionary search that could potentially be used in such applications. First, we present a method of automatically generating analog circuit designs using evolutionary search and a circuit construction language. Our system allows circuit size (number of devices), circuit topology, and device values to be evolved. Using a parallel genetic algorithm, we present experimental results for five design tasks. Second, we investigate the use of coevolution in automated circuit design. We examine fitness evaluation by comparing the effectiveness of four fitness schedules. The results indicate that solution quality is highest with static and co-evolving fitness schedules as compared to the other two dynamic schedules. We discuss these results and offer two possible explanations for the observed behavior: retention of useful information, and alignment of problem difficulty with circuit proficiency.

Lohn, Jason D.↗