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At least 1,495 records · Page 83
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Integrated Computational System for Aerodynamic Steering and Visualization

In February of 1994, an effort from the Fluid Dynamics and Information Sciences Divisions at NASA Ames Research Center with McDonnel Douglas Aerospace Company and Stanford University was initiated to develop, demonstrate, validate and disseminate automated software for numerical aerodynamic simulation. The goal of the initiative was to develop a tri-discipline approach encompassing CFD, Intelligent Systems, and Automated Flow Feature Recognition to improve the utility of CFD in the design cycle. This approach would then be represented through an intelligent computational system which could accept an engineer's definition of a problem and construct an optimal and reliable CFD solution. Stanford University's role focused on developing technologies that advance visualization capabilities for analysis of CFD data, extract specific flow features useful for the design process, and compare CFD data with experimental data. During the years 1995-1997, Stanford University focused on developing techniques in the area of tensor visualization and flow feature extraction. Software libraries were created enabling feature extraction and exploration of tensor fields. As a proof of concept, a prototype system called the Integrated Computational System (ICS) was developed to demonstrate CFD design cycle. The current research effort focuses on finding a quantitative comparison of general vector fields based on topological features. Since the method relies on topological information, grid matching and vector alignment is not needed in the comparison. This is often a problem with many data comparison techniques. In addition, since only topology based information is stored and compared for each field, there is a significant compression of information that enables large databases to be quickly searched. This report will (1) briefly review the technologies developed during 1995-1997 (2) describe current technologies in the area of comparison techniques, (4) describe the theory of our new method researched during the grant year (5) summarize a few of the results and finally (6) discuss work within the last 6 months that are direct extensions from the grant.

Hesselink, Lambertus↗
NASA NTRS2013

Integrated Tools for Future Distributed Engine Control Technologies

Turbine engines are highly complex mechanical systems that are becoming increasingly dependent on control technologies to achieve system performance and safety metrics. However, the contribution of controls to these measurable system objectives is difficult to quantify due to a lack of tools capable of informing the decision makers. This shortcoming hinders technology insertion in the engine design process. NASA Glenn Research Center is developing a Hardware-inthe- Loop (HIL) platform and analysis tool set that will serve as a focal point for new control technologies, especially those related to the hardware development and integration of distributed engine control. The HIL platform is intended to enable rapid and detailed evaluation of new engine control applications, from conceptual design through hardware development, in order to quantify their impact on engine systems. This paper discusses the complex interactions of the control system, within the context of the larger engine system, and how new control technologies are changing that paradigm. The conceptual design of the new HIL platform is then described as a primary tool to address those interactions and how it will help feed the insertion of new technologies into future engine systems.

Culley, Dennis↗
NASA NTRS2013

Micro-Spec: An Ultra-Compact, High-Sensitivity Spectrometer for Far-Infrared and Sub-Millimeter Astronomy

High-performance, integrated spectrometers operating in the far-infrared and sub-millimeter promise to be powerful tools for the exploration of the epochs of reionization and initial galaxy formation. These devices, using high-efficiency superconducting transmission lines, can achieve the performance of a meter-scale grating spectrometer in an instrument implemented on a four-inch silicon wafer. Such a device, when combined with a cryogenic telescope in space, provides an enabling capability for studies of the early universe. Here, the optical design process for Micro-Spec (mu-Spec) is presented, with particular attention given to its two-dimensional diffractive region, where the light of different wavelengths is focused on the different detectors. The method is based on the stigmatization and minimization of the light path function in this bounded region, which results in an optimized geometrical configuration. A point design with an efficiency of approx. 90% has been developed for initial demonstration, and can serve as the basis for future instruments. Design variations on this implementation are also discussed, which can lead to lower efficiencies due to diffractive losses in the multimode region.

spectroscopic instrumentation↗
NASA NTRS2014

Micro-Spec: An Ultracompact, High-sensitivity Spectrometer for Far-Infrared and Submillimeter Astronomy

High-performance, integrated spectrometers operating in the far-infrared and submillimeter ranges promise to be powerful tools for the exploration of the epochs of reionization and initial galaxy formation. These devices, using high-efficiency superconducting transmission lines, can achieve the performance of a meter-scale grating spectrometer in an instrument implemented on a 4 inch silicon wafer. Such a device, when combined with a cryogenic telescope in space, provides an enabling capability for studies of the early universe. Here, the optical design process for Micro-Spec (micron-Spec) is presented, with particular attention given to its two-dimensional diffractive region, where the light of different wavelengths is focused on the different detectors. The method is based on the stigmatization and minimization of the light path function in this bounded region, which results in an optimized geometrical configuration. A point design with an efficiency of (is) approximately 90% has been developed for initial demonstration and can serve as the basis for future instruments. Design variations on this implementation are also discussed, which can lead to lower efficiencies due to diffractive losses in the multimode region.

cryogenic telescope↗
NASA NTRS2021

Generation-based Evolutionary Tool for the Optimization of Constellations (GenETOC)

With the rapid growth in the capabilities of smaller satellites, satellite architectures that replace a single, extremely capable spacecraft with multiple, cheaper ones are gaining in popularity. Unfortunately, the orbit design process for constellations can be significantly more involved, especiallywhen the relative placement of the individual spacecraft within the constellation is not constrained by mission and/or science objectives. Optimizing a satellite constellation in the presence of multiple, competing objectives is a highly complex problem to which many traditional mathematical optimization methods cannot be applied and few tools exist to help mission designers search for promising candidate mission designs. The Generation-based Evolutionary Tool for the Optimization of Constellations (GenETOC) has been created to search for near-optimal constellation design options. GenETOC combines a modified version of the Non-dominated Sorting Genetic Algorithm II (NSGA II) with STK Components libraries (a 3rdparty .NET package created by Analytical Graphics Inc.) to create a framework that enables a mission designer to generate a simulation that models the design problem and obtain a family of potential, near-optimal solutions that can be investigated more in detail.

mission design↗
DOE OSTI2019

CatCost™ (Catalyst Cost Estimation Tool) [SWR-18-74]

CatCost™ is a state-of-the-art cost estimation tool designed to reduce the cost uncertainty associated with pre-commercial catalyst materials. The tool combines industry-standard cost estimation methods and resources into an intuitive suite of tools to bring actionable cost insight to every step of catalyst research and development. CatCost™ allows the rapid development of comprehensive catalyst cost estimates. It incorporates detailed insight into manufacturing methods, especially for pre-commercial catalysts, without requiring any process design experience. The tool has been designed from the ground up with a number of user-selectable estimation methods, pricing libraries, and ease-of-use features to tailor an estimate to a user's skill level and need for customization, empowering researchers of all skill-levels to make better R&D decisions throughout the catalyst development cycle. Our costing methods are fully transparent and enable power-users the ability to adjust any estimate to the economic realities of their operation. The tool has been designed from the ground up with a number of user-selectable estimation methods, pricing libraries, and ease-of-use features to tailor an estimate to a user's skill level and need for customization, empowering researchers of all skill-levels to make better R&D decisions throughout the catalyst development cycle. Our costing methods are fully transparent and enable power-users the ability to adjust any estimate to the economic realities of their operation. Features include: Raw materials pricing: Libraries of common chemicals, cost scaling indices, guidance for obtaining bulk quotes, and methods for extrapolating laboratory-scale prices to bulk. Simplified step method for synthesis by a contract manufacturer: All-in hourly cost for process equipment using methods and data from tollers. (Excel-only in v1.0)

Baddour, Frederick↗
NASA NTRS2003

Probabilistic Evaluation of Advanced Ceramic Matrix Composite Structures

The objective of this report is to summarize the deterministic and probabilistic structural evaluation results of two structures made with advanced ceramic composites (CMC): internally pressurized tube and uniformly loaded flange. The deterministic structural evaluation includes stress, displacement, and buckling analyses. It is carried out using the finite element code MHOST, developed for the 3-D inelastic analysis of structures that are made with advanced materials. The probabilistic evaluation is performed using the integrated probabilistic assessment of composite structures computer code IPACS. The affects of uncertainties in primitive variables related to the material, fabrication process, and loadings on the material property and structural response behavior are quantified. The primitive variables considered are: thermo-mechanical properties of fiber and matrix, fiber and void volume ratios, use temperature, and pressure. The probabilistic structural analysis and probabilistic strength results are used by IPACS to perform reliability and risk evaluation of the two structures. The results will show that the sensitivity information obtained for the two composite structures from the computational simulation can be used to alter the design process to meet desired service requirements. In addition to detailed probabilistic analysis of the two structures, the following were performed specifically on the CMC tube: (1) predicted the failure load and the buckling load, (2) performed coupled non-deterministic multi-disciplinary structural analysis, and (3) demonstrated that probabilistic sensitivities can be used to select a reduced set of design variables for optimization.

Abumeri, Galib H.↗
DOE OSTI2022

Additive Manufacturing Flaw Assessment Methodology

An evolution fatigue data and flaw tolerance of components produced using the Powder Bed Fusion (PBF) Additive Manufacturing (AM) process is documented in this report. Initial differences in fatigue data for AM components compared to smooth bar fatigue data indicated a need for a more detailed analysis of AM data available in technical literature. The investigation was initiated to support the development of a fatigue analysis methodology for AM components to support the of codification of AM technology for pressure equipment. The project was initiated to collect and analyze stainless steel 304L and 316L AM fatigue test data and corresponding process and quality information to develop S-N and E-N based fatigue data representation. Additional AM fatigue test data including Inconel Ti-6-4 and aluminum alloys were also considered for comparison purposes Metallic AM parts tend to contain various forms of defects distributed throughout the part. If an AM part is subjected to fatigue loading in service, a fatigue analysis needs to be performed during the design process to ensure an acceptable service life for the part. Post-process machining and polishing do not to improve fatigue resistance in any significant degree. The low cycle fatigue regime is of particular interest to this project in support of flaw acceptance criteria currently under development by ASME’s BPTCS/BNCS. Internal defects become exposed as external surface defects during machining for the machining of the AM part to final dimensions. This implies that as long as inherent AM defects are within a controlled limit in terms of both size and distribution characteristics, the corresponding fatigue test data in terms of either S-N (stress life) or E-N (strain life) can be investigated and characterized to establish fatigue properties of AM parts for design and fatigue evaluation purposes. The resulting S-N or E-N curves and their scatter bands can be used to derive fatigue design allowable stress values by capturing the effects of distributed discontinuities within an acceptable limit.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Parametric Optimization of Rigid Wheels for Planetary Surface Mobility Applications

Design-Build-Test approaches for spaceflight hardware are time and cost intensive, which can result in suboptimal mechanism designs. Optimization-based approaches that utilize high-fidelity models and physics simulation could overcome these limitations while simultaneously speeding up the mechanical design process and reducing cost. In this work, we present a toolchain that enables the multi-objective optimization of rigid rover wheels for planetary surface mobility applications. The toolchain uses Chrono’s Continuous Representation Model (CRM) functionality to simulate granular soil and performs multi-objective parametric optimization on candidate rover wheels to meet a desired performance criterion. The resulting wheel design is then evaluated experimentally using a single-wheel testbed. We end with a discussion of how the toolchain can be extended to simultaneously co-optimize other system parameters, such as system power consumption and feedback control gains.

Optimization↗
DOE OSTI2020

ZAM Modeling Study to Support the Tank Closure Cesium Removal (TCCR) 1A Unit

Currently at the Savannah River Site (SRS), the Tank Closure Cesium Removal (TCCR) is an “at-tank” process designed to remove cesium from aqueous tank waste. Cesium will be removed by ion exchange using the engineered IONSIV® R9120 form of Crystalline Silicotitanate (CST) media. The current TCCR design has two columns online in a lead-lag configuration to optimize media usage and achieve the target decontamination. Once the lead column is saturated with cesium, it will be removed from service, the lag column will rotate into the lead position, and a new column with fresh ion-exchange media will be placed into the lag position. The TCCR process for cesium removal from Tank 10H is detailed in X-SOW-H- 00002. Demonstration of the system began in early calendar year 2019 with two batches of salt solution generated by dissolving saltcake in Tank 10H, followed by processing of these batches through the TCCR system. A third TCCR Tank 10H dissolved saltcake batch is scheduled for processing soon. Upon completion of the demonstration with Tank 10H dissolved saltcake, Tank 9H salt solution will be transferred to Tank 10H and subsequently processed through the TCCR unit with new CST media (referred to as R9120-B 30x60) added to new IX columns. The TCCR processing campaign of Tank 9H salt solution is referred to as TCCR-1A .

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Practical and Optimal Sequential Bayesian Experimental Design for Complex Systems Incorporating Human Experimenter Preferences (Final Scientific/Technical Report)

Experiments are indispensable for developing models of complex systems. Carefully designed experiments can provide substantial savings for these expensive data-acquisition opportunities. However, designs based on heuristics are often suboptimal for systems with multiphysics, nonlinear dynamics, and uncertain and noisy environments. Optimal experimental design, while leveraging predictive models, seeks to systematically quantify and maximize the value of experiments. In this project, we focused on the design of multiple experiments, where current approaches are largely suboptimal: batch-design does not adapt to new data acquired during the experiment campaign (no feedback), and greedy/myopic design ignores future dynamics and consequences (no lookahead). We developed the mathematical framework and computational methods for sequential optimal experimental design (sOED) for complex systems. We enabled tractable model-based sOED in a rigorous manner through novel algorithms based on reinforcement learning, and investigated the effects of human experimenters on the design process. Our methods are fully Bayesian, able to quantify and update uncertainty in a principled manner. The traits aimed by our approach—mathematical rigor and optimality, human effects and uncertainty quantification, computational practicality—are crucial for elevating the standards of artificial intelligence (AI) to support decision-making in scientific domains, and contribute toward trust and realistic adoption of AI in experimental design practice.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1989

Summary of activities

Four space projects' activities are summarized. Design work on the Mars Penetrator Project, in cooperation with the NASA Ames Research Center, is being continued. Efforts are focused on the drilling mechanism which must penetrate the martian subsurface soil to collect and retrieve an uncontaminated sample. The new design consists of a rotary-percussive drill mechanism. This mechanism is optimum for dry drilling, necessary to avoid contamination of the soil sample, in many different soil types. The need for a small, relatively inexpensive device to study the chemical structure of this martian soil was also established. The egg design was chosen for its low cost compared to other systems and potential for a large number of eggs to be deployed on the martian surface. The design process included analysis of the dynamics of reentry, dissipation of heat during reentry, impact with the surface, access to undisturbed soil samples, and ability to gather samples from the soil at three depths. The egg consists of the reentry systems, soil probe lifting system, soil probe package, gas chromatograph, transmitter, and battery power supply. The egg must function only once, but is designed to withstand one martian year. The Mars Mole is designed as a rover-based device which penetrates the martian soil to a depth of up to 10 m, obtains a sample of soil, and returns it to the surface for analysis. The mole was designed to meet the following specifications: (1) weight less than 10 kg; (2) size less than 20 x 20 x 30 cm; (3) power less than 100 W; (4) ability to obtain a sample of at least 5 cc; (5) ability to penetrate fine, loose sand; and (6) need to obtain at least one sample. The space station umbilical connector project is a device which provides the translational motion of the connectors on the Space Station Freedom to allow engagement for power and data transfer. The design is capable of delivering a 20 lb force within the necessary tolerances and will operate reliably in the space environment.

Source record↗
NASA NTRS2009

Compositional Verification of a Communication Protocol for a Remotely Operated Vehicle

This paper presents the specification and verification in the Prototype Verification System (PVS) of a protocol intended to facilitate communication in an experimental remotely operated vehicle used by NASA researchers. The protocol is defined as a stack-layered com- position of simpler protocols. It can be seen as the vertical composition of protocol layers, where each layer performs input and output message processing, and the horizontal composition of different processes concurrently inhabiting the same layer, where each process satisfies a distinct requirement. It is formally proven that the protocol components satisfy certain delivery guarantees. Compositional techniques are used to prove these guarantees also hold in the composed system. Although the protocol itself is not novel, the methodology employed in its verification extends existing techniques by automating the tedious and usually cumbersome part of the proof, thereby making the iterative design process of protocols feasible.

Goodloe, Alwyn E.↗
NASA NTRS1987

Measurement science and manufacturing science research

The research program of Semiconductor Research Corp. is managed as three overlapping areas: Manufacturing Sciences, Design Sciences and Microstructure Sciences. A total of 40 universities are participating in the performance of over 200 research tasks. The goals and direction of Manufacturing Sciences research became more clearly focused through the efforts of the Manufacturing Sciences Committee of the SRC Technical Advisory Board (TAB). The mission of the SRC Manufacturing Research is the quantification, control, and understanding of semiconductor manufacturing process necessary to achieve a predictable and profitable product output in the competitive environment of the next decade. The 1994 integrated circuit factory must demonstrate a three level hierarchy of control: (1) operation control, (2) process control, and (3) process design. These levels of control are briefly discussed.

Phillips, D. Howard↗
NASA NTRS2009

Modeling and Simulation of the Second-Generation Orion Crew Module Air Bag Landing System

Air bags were evaluated as the landing attenuation system for earth landing of the Orion Crew Module (CM). An important element of the air bag system design process is proper modeling of the proposed configuration to determine if the resulting performance meets requirements. Analysis conducted to date shows that airbags are capable of providing a graceful landing of the CM in nominal and off-nominal conditions such as parachute failure, high horizontal winds, and unfavorable vehicle/ground angle combinations. The efforts presented here surround a second generation of the airbag design developed by ILC Dover, and is based on previous design, analysis, and testing efforts. In order to fully evaluate the second generation air bag design and correlate the dynamic simulations, a series of drop tests were carried out at NASA Langley's Landing and Impact Research (LandIR) facility. The tests consisted of a full-scale set of air bags attached to a full-scale test article representing the Orion Crew Module. The techniques used to collect experimental data, construct the simulations, and make comparisons to experimental data are discussed.

Timmers, Richard B.↗
DOE OSTI2025

Predicting Initial Trans-Membrane Pressure for Optimized Operations in UF Unit Using Random Forest

With the growing scarcity of freshwater, innovative process design mechanisms like Ultra-filtration(UF) units are increasingly gaining attention among water treatment utilities to address the rising demand. Ensuring reliable water production necessitates efficient resource utilization, minimizing downtime in UF systems. Recent advancements in machine learning (ML) have enabled the development of accurate data-driven models for Model Predictive Control (MPC), often requiring minimal prior knowledge of underlying physical processes. In this study, we present predictive regression models based on Random Forest (RF) and Auto-Regressive (AR) approaches to forecast the initial Trans-Membrane Pressure (TMP) for each filtration cycle in data generated by Direct Potable Reuse (DPR) systems. The proposed RF-based model demonstrates superior performance compared to baseline methods, including historical mean, Last Observation Carried Forward (LOCF), and naïve AR models, across various forecasting horizons in terms of root mean square (RMSE) metric. Accurate prediction of initial TMP is critical for optimizing CCRO operations, as it enables the development of robust modelling frameworks that enhance process efficiency and reliability. The demonstrated efficacy of the RF-based approach highlights its potential as a tool for real-time decision-making in water treatment systems, paving the way for advanced process optimization and sustainable water resource management.

Mukherjee, Subrata [ORNL] (ORCID:0000000309930338)↗
DOE OSTI2025

Predicting Initial Trans-Membrane Pressure for Optimized Operations in UF Unit Using Random Forest

With the growing scarcity of freshwater, innovative process design mechanisms like Reverse Osmosis (RO) are increasingly gaining attention among water treatment utilities to address the rising demand. Ensuring reliable water production necessitates efficient resource utilization, minimizing downtime in (ultra-filtration) UF systems. Recent advancements in machine learning (ML) have enabled the development of accurate data-driven models for Model Predictive Control (MPC), often requiring minimal prior knowledge of underlying physical processes. In this study, we present predictive regression models based on Random Forest (RF) and Auto-Regressive (AR) approaches to forecast the initial Trans-Membrane Pressure (TMP) for each filtration cycle in data generated by Direct Potable Reuse (DPR) systems. The proposed RF-based model demonstrates superior performance compared to baseline methods, including historical mean, Last Observation Carried Forward (LOCF), and naïve AR models, across various forecasting horizons in terms of root mean square error (RMSE) metric. To evaluate how different classes of process variables contribute to TMP dynamics over time, we examine the feature importance of independent covariates across multiple forecast horizons. This analysis provides insight into the temporal relevance of operational and sensor-derived features, guiding control and monitoring strategies. Additionally, the impact of hyperparameter tuning on TMP prediction performance is studied for both direct and recursive RF modelling approaches across increasing forecast horizons. Accurate prediction of initial TMP is critical for optimizing RO operations, as it enables the development of robust modelling frameworks by accurately estimating membrane fouling trends, thereby enhancing process efficiency and long-term reliability. The demonstrated efficacy of the RF-based approach highlights its potential as a tool for real-time decision-making in water treatment systems, paving the way for advanced process optimization and sustainable water resource management.

Mukherjee, Subrata [ORNL] (ORCID:0000000309930338)↗