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At least 1,405 records · Page 78

Simulating a small turboshaft engine in real-time multiprocessor simulator (RTMPS) environment

A Real-Time Multiprocessor Simulator (RTMPS) has been developed at NASA Lewis Research Center. The RTMPS uses parallel microprocessors to achieve computing speeds needed for real-time engine simulation. This report describes the use of the RTMPS system to simulate a small turboshaft engine. The process of programming the engine equations and distributing them over one, two, and four processors is discussed. Steady-state and transient results from the RTMPS simulation are compared with results from a main-frame-based simulation. Processor execution times and the associated execution time savings for the two and four processor cases are presented using actual data obtained from the RTMPS system. Included is a discussion of why the minimum achievable calculation time for the turboshaft engine model was attained using four processors. Finally, future enhancements to the RTMPS system are discussed including the development of a generalized partitioning algorithm to automatically distribute the system equations among the processors in optimum fashion.

Milner, E. J.↗

Space crew radiation exposure analysis system based on a commercial stand-alone CAD system

Major improvements have recently been completed in the approach to spacecraft shielding analysis. A Computer-Aided Design (CAD)-based system has been developed for determining the shielding provided to any point within or external to the spacecraft. Shielding analysis is performed using a commercially available stand-alone CAD system and a customized ray-tracing subroutine contained within a standard engineering modeling software package. This improved shielding analysis technique has been used in several vehicle design projects such as a Mars transfer habitat, pressurized lunar rover, and the redesigned Space Station. Results of these analyses are provided to demonstrate the applicability and versatility of the system.

Appleby, Matthew H.↗

A Formal Approach for Designing and Evaluating Procedures

Operator interaction with modern control systems is a topic of great concern in high-risk industries such as nuclear power and commercial aviation. The issues associated with such systems focus on the ability of the operators (e.g., pilots) to achieve mission goals safely while containing failures. Operators must be able to interact safely and reliably with highly automatic and complex systems across the full spectrum of possible operating conditions, including normal, abnormal, and emergency situations. In environments such as commercial aviation, operator interaction with the machine is specified through a set of standard operating procedures (SOP). A procedure represents a collective agreement on the 'best' way to perform a given task. The intent of this paper is to suggest a formal methodology, for designing and evaluating procedures, that is both reliable and systematic. Our approach involves two major elements: a model of the machine and a list of the operator's task specifications (goals). We use formal modeling paradigms for describing the system and super-imposing on it the operator's tasks. Such paradigms, based on recent frameworks such as Statecharts and Hierarchical Hybrid Machines appear to be adequate methods for analyzing operator interaction with modern control systems. To illustrate this methodology, we model and analyze the sequence of actions for an emergency procedure. The procedure, Irregular Engine Start, for a medium-range aircraft, specifies the sequence of immediate actions that must be performed by the crew to avoid an uncontrolled rise in engine temperature during start-up. A model of engine behavior during a hot start is constructed. It also describes the various actions that can be taken by the crew and the resulting outcomes. The model is then opened up as a tree of all possible action sequences. This action tree allows us to trace the correct sequences necessary to achieve the desired end-goal (secure and shut down of the engine). In conclusion, we argue that the current process of designing and evaluating procedures can be improved. We discuss the implications of this approach for designing and evaluating this and other types of procedures. We conclude with insights about the benefits and limitation of this methodology, and offer suggestions for future research.

Degani, Asaf↗

Quantifying the Impact of Systems Interdependencies in Space Systems Architectures

Due to the high number of systems in a space mission architecture and to their complex interactions, identifying risk and critical operational dependencies is not obvious. Traditional systems engineering methodology and risk assessment does not capture the impact of interactions between systems nor the cascading effects of disruptions. Based on these considerations, the Systems Operational Dependency Analysis methodology was developed for use by systems analysts and decision makers. This methodology utilizes a parametric model of interdependencies between systems to quantify the direct and indirect impact of system disruptions on other systems, as well as identify root causes. The results are effective at providing decision support for prioritizing technology investment based on risk reduction associated with potential system disruptions. Expanding on research presented at IAC 2018 and based on a collaboration with NASA Marshall Space Flight Center, this paper applies the Systems Operational Dependency Analysis methodology to NASA Lunar Gateway in collaboration with NASA’s lunar exploration plans. The paper presents a hierarchical representation of the interdependencies between a Gateway habitat’s systems and subsystems, demonstrates quantification of the impact of disruption, and assesses the criticality of the constituent systems and subsystems.

Guariniello, Cesare↗

Model predictive control of a lean-burn gasoline engine coupled with a passive selective catalytic reduction system

Lean-burn gasoline engines have demonstrated 10–20% engine efficiency gain over stoichiometric engines and are widely considered as a promising technology for meeting the 54.5 miles-per-gallon (mpg) Corporate Average Fuel Economy standard by 2025. Nevertheless, NOx emissions control for lean-burn gasoline for meeting the stringent EPA Tier 3 emission standards has been one of the main challenges towards the commercialization of highly-efficient lean-burn gasoline engines in the United States. Passive selective catalytic reduction (SCR) systems, which consist of a three-way catalyst and SCR, have demonstrated great potentials of effectively reducing NOx emissions for lean gasoline engines but may cause significant fuel penalty due to ammonia generation via rich engine combustion. The purpose of this study is to develop a model-predictive control (MPC) scheme for a lean-burn gasoline engine coupled with a passive SCR system to minimize the fuel penalty associated with passive SCR operation while satisfying stringent NOx and NH3 emissions requirements. Simulation results demonstrate that the MPC-based control can reduce the fuel penalty by 47.7% in a simulated US06 cycle and 32.0% in a simulated UDDS cycle, compared to the baseline control, while achieving over 96% deNOx efficiency and less than 15 ppm tailpipe ammonia slip. The proposed MPC control can potentially enable high engine efficiency gain for highly-efficient lean-burn gasoline engine while meeting the stringent EPA Tier 3 emission standards.

Chen, Pingen↗

Comprehensive Environmental Informatics System (CEIS) Integrating Crew and Vehicle Environmental Health

Integrated Vehicle Health Management (IVHM) systems have been pursued as highly integrated systems that include smart sensors, diagnostic and prognostics software for assessments of real-time and life-cycle vehicle health information. Inclusive to such a system is the requirement to monitor the environmental health within the vehicle and the occupants of the vehicle. In this regard an enterprise approach to informatics is used to develop a methodology entitled, Comprehensive Environmental Informatics System (CEIS). The hardware and software technologies integrated into this system will be embedded in the vehicle subsystems, and maintenance operations, to provide both real-time and life-cycle health information of the environment within the vehicle cabin and of its occupants. This comprehensive information database will enable informed decision making and logistics management. One key element of the CEIS is interoperability for data acquisition and archive between environment and human system monitoring. With comprehensive components the data acquired in this system will use model based reasoning systems for subsystem and system level managers, advanced on-board and ground-based mission and maintenance planners to assess system functionality. Knowledge databases of the vehicle health state will be continuously updated and reported for critical failure modes, and routinely updated and reported for life cycle condition trending. Sufficient intelligence, including evidence-based engineering practices which are analogous to evidencebased medicine practices, will be included in the CEIS to result in more rapid recognition of off-nominal operation to enable quicker corrective actions. This will result from better information (rather than just data) for improved crew/operator situational awareness, which will produce significant vehicle and crew safety improvements, as well as increasing the chance for mission success, future mission planning as well as training. Other benefits include improved reliability, increase safety in operations and cost of operations. The cost benefits stem from significantly reduced processing and operations manpower, predictive maintenance for systems and subjects. The improvements in vehicle functionality and cost will result from increased prognostic and diagnostic capability due to the detailed total human exploration system health knowledge from CEIS. A collateral benefit is that there will be closer observations of the vehicle occupants as wrist watch sized devices are worn for continuous health monitoring. Additional database acquisition will stem from activities in countermeasure practices to ensure peak performance capability by occupants of the vehicle. The CEIS will provide data from advanced sensing technologies and informatics modeling which will be useful in problem troubleshooting, and improving NASA s awareness of systems during operation.

Nall, Mark E.↗

Systems Biology-Based Optimization of Extremely Thermophilic Lignocellulose Conversion to Bioproducts

This was a collaborative project involving researchers at the University of Georgia, North Carolina State University, Sanford‐Burnham‐Prebys Med. Discovery Institute and the University of Rhode Island. The over-arching goal was to demonstrate that non-model microorganisms, specifically extreme thermophiles, can be a strategic metabolic engineering platform for industrial biotechnology. We engineered the most thermophilic lignocellulose-degrading organism known, Caldicellulosiruptor bescii (Cbes) , which grows optimally near 80°C, and the most thermophilic fermentative organism known, Pyrococcus furiosus (Pfu) , which grows optimally at 100°C, to produce several key industrial chemicals. This work leveraged recent breakthrough advances in the development of molecular genetic tools for these organisms, complemented by a deep understanding of its metabolism and physiology gained over the past decade of study in the PIs’ laboratories. We applied the latest metabolic reconstruction and modeling approaches to optimize biomass to product conversion. Bio-processing above 70°C can have important advantages over near-ambient operations. Highly genetically-modified microorganisms usually have a fitness disadvantage and can be easily overtaken in culture when contaminating microbes are present. The high growth temperature of extreme thermophiles precludes growth or survival of virtually any contaminating organism or phage. This reduces operating costs associated with reactor sterilization and maintaining a sterile facility. In addition, at industrial scales, heat production from microbial metabolic activity vastly outweighs heat loss through bioreactor walls such that cooling is required. Extreme thermophiles have the advantage that non-refrigerated cooling water can be used if needed, and heating requirements can be met with low-grade steam typically in excess capacity on plant sites. We assembled a highly interdisciplinary team that brought together all of the expertise for the project to have successful outcomes. This project also built upon and utilized extensive information already available in the PIs’ labs for both Cbes and Pfu to develop models that provide a comprehensive description of these organisms’ physiology and metabolism that were utilized to inform metabolic engineering strategies. The models were validated with experimental data and the results demonstrated that unpretreated lignocellulose has the potential to be converted into value-added industrial chemicals at high loading at bioreactor scale. The data generated from this research were published in twenty-one peer-reviewed papers in international journals with online access.

60 APPLIED LIFE SCIENCES↗

An estimate of the second law thermodynamic efficiency of the various units comprising an Environmental Control and Life Support System (ECLSS)

The objective of this paper is to present an estimate of the second law thermodynamic efficiency of the various units comprising an Environmental Control and Life Support System (ECLSS). The technique adopted here is based on an evaluation of the 'lost work' within each functional unit of the subsystem. Pertinent information for our analysis is obtained from a user interactive integrated model of an ECLSS. The model was developed using ASPEN. A potential benefit of this analysis is the identification of subsystems with high entropy generation as the most likely candidates for engineering improvements. This work has been motivated by the fact that the design objective for a long term mission should be the evaluation of existing ECLSS technologies not only the basis of the quantity of work needed for or obtained from each subsystem but also on the quality of work. In a previous study Brandhorst showed that the power consumption for partially closed and completely closed regenerable life support systems was estimated as 3.5 kw/individual and 10-12 kw/individual respectively. With the increasing cost and scarcity of energy resources, our attention is drawn to evaluate the existing ECLSS technologies on the basis of their energy efficiency. In general the first law efficiency of a system is usually greater than 50 percent. From literature, the second law efficiency is usually about 10 percent. The estimation of second law efficiency of the system indicates the percentage of energy degraded as irreversibilities within the process. This estimate offers more room for improvement in the design of equipment. From another perspective, our objective is to keep the total entropy production of a life support system as low as possible and still ensure a positive entropy gradient between the system and the surroundings. The reason for doing so is as the entropy production of the system increases, the entropy gradient between the system and the surroundings decreases, and the system will gradually approach equilibrium with the surroundings until it reaches the point where the entropy gradient is zero. At this point no work can be extracted from the system. This is called the 'dead state' of the system.

Chatterjee, Sharmista↗

Enhancing Operational Safety via Agentic Dialogue Hazard Identification Analysis

Operational safety in high-stakes domains such as industrial process control, autonomous, and safety-critical systems demand reliable hazard identification. While large language models (LLMs) have shown promise in automating safety analysis tasks, single-turn, monolithic inference is brittle: it lacks the self-correction, deliberation, and contextual refinement that safety engineers apply iteratively. In this paper, we introduce HAZDIAL, a framework that investigates whether structured agentic dialogue (multi-agent, multi-turn interactions) improves the quality of NLP-based hazard identification over single-pass baselines. We systematically compare two dialogue modalities: adversarial debate and constructive discussion, and propose an genetic algorithm-based agentic interaction optimization. We evaluate all configurations against a curated golden dataset using standard classification metrics (accuracy, precision, recall, F1) and a novel dialogue metrics. This work advances the intersection of dialogue systems, multi-agent reasoning, and AI safety, providing empirical evidence for dialogue-driven hazard analysis.

Das, Sanjay [ORNL] (ORCID:0009000542591915)↗

Development of a scintillator based fast-ion loss detector for the Wendelstein 7-X stellarator

A new scintillator based fast-ion loss detector (FILD) system has been designed for the Wendelstein 7-X (W7-X) stellarator. The mechanical design of the system is presented here along with engineering analyses of the system. This includes an assessment of the structural loads which also considers electromagnetic forces calculated for possible disruption scenarios as well as a mode frequency analysis of the system. Furthermore, an analysis of the thermal characteristics of the actively cooled probe head under prescribed steady state and transient heat loads is presented. Finally, the optical relay system is described and its properties used to forward model synthetic camera signals using the FILDSIM code and based on theoretical fast-ion losses incident on the probe head calculated using the ASCOT5 code.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Applications of the Dulmage–Mendelsohn decomposition for debugging nonlinear optimization problems

Nonlinear modeling and optimization is a valuable tool for aiding decisions by engineering practitioners, but programming an optimization problem based on a complex electrical, mechanical, or chemical process is a time-consuming and error-prone activity. Therefore, there is a need for model analysis and debugging tools that can detect and diagnose modeling errors. One such tool is the Dulmage–Mendelsohn decomposition, which identifies structurally under- and over-determined subsets in systems of equations and variables by partitioning the bipartite graph of the system. This work provides the necessary background to understand the Dulmage–Mendelsohn decomposition and its application to the analysis of nonlinear optimization problems, demonstrates its use in diagnosing a variety of modeling errors, and introduces software implementations for analyzing nonlinear optimization problems in the Pyomo and JuMP algebraic modeling languages.

42 ENGINEERING↗

Cycloidal Shaping of Polyhedra in Two-Rotor Systems

A method of solution is proposed for the model of the cycloid shaping of polyhedra. The method is based on reducing the equations to algebraic form by polynomial approximation of transcendental functions.

42 ENGINEERING↗

SetGo: Metadata Readiness for Scientific AI Datasets

Scientific datasets intended for AI use require both computational readiness for model training and metadata readiness for discovery, sharing, and reuse. The Readiness Engine for Data Integration (REDI) addresses computational readiness, but no corresponding tool evaluates whether a dataset’s metadata are sufficiently complete, governed, and standards-compliant for publication and agent-based consumption. Existing FAIR assessors operate only on published repository records, and no single system covers FAIR compliance, licensing, provenance, governance, reproducibility, and catalog readiness together. We present SetGo, an open-source Python toolkit that assesses and repairs metadata readiness across these six dimensions before a dataset is published or archived. Applied to four scientific corpora, SetGo surfaces deficiencies that general-purpose tools do not detect: ERA5 climate metadata scores 4% on ACDD 1.3 compliance; materials datasets fail OPTIMADE species-definition requirements; and PDB-derived proteomics data carries licensing terms incompatible with standard SPDX identifiers. Guided enrichment raises overall FAIR scores from 52–57% to 81–91%, and a single setgo publish command pushes to Hugging Face Hub, CKAN, or OpenMetadata with ML Commons Croissant 1.0 metadata sidecars. To support interactive and automated workflows, SetGo integrates with coding agents powered by large language models (LLMs) through a /setgo skill that enables natural-language execution of the full assess–enrich–publish loop, with user involvement limited to supplying missing metadata values.

Wilkinson, Sean [ORNL] (ORCID:0000000214437479)↗

Modeling Heat Transfer and Pressurization of Polymeric Methylene Diisocyanate (PMDI) Polyurethane Foam in a Sealed Container

Polymer foam encapsulants provide mechanical, electrical, and thermal isolation in engineered systems. It can be advantageous to surround objects of interest, such as electronics, with foams in a hermetically sealed container to protect the electronics from hostile environments, such as a crash that produces a fire. However, in fire environments, gas pressure from thermal decomposition of foams can cause mechanical failure of the sealed system. In this work, a detailed study of thermally decomposing polymeric methylene diisocyanate (PMDI)-polyether-polyol based polyurethane foam in a sealed container is presented. Both experimental and computational work is discussed. Three models of increasing physics fidelity are presented: No Flow, Porous Media, and Porous Media with VLE. Each model us described in detail, compared to experiment, and uncertainty quantification is performed. While the Porous Media with VLE model matches has the best agreement with experiment, it also requires the most computational resources.

36 MATERIALS SCIENCE↗

Mathematical Programming Models for Shale Oil & Gas Development: A Review and Perspective

Here, in this paper, we provide a comprehensive review of mathematical programming models for shale oil & gas development, and we offer a perspective on outstanding research opportunities. We distinguish contributions in five major topic areas, namely: (1) development planning, (2) water management, (3) production optimization, (4) supplies, gathering & processing, and (5) life cycle analysis & sustainability. We highlight how various types of mathematical programming models (i.e., linear programs, nonlinear programs, mixed-integer linear programs, mixed-integer nonlinear programs) have been proposed primarily by the Process Systems Engineering community to address the respective decision-making problems, and we highlight instances of successful deployment in industry. Finally, based on a critical assessment of the existing body of work, we identify opportunities for future research across the major topic areas.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An analysis of the takeoff and landing performance of a jet-powered STOL augmentor wing design

A preliminary study of the takeoff and landing performance characteristics of a swept wing airplane with augmented jet flap, designed for STOL operation and low noise is presented. The study is based on aerodynamic data from wind tunnel tests of a large-scale swept augmentor wing model, scaled up to a 48,000 pound airplane. Engine characteristics are based on a turbo fan with a fan pressure ratio of 2.5 delivering the major portion of the thrust to the augmentor flap. A description of the overall airplane configuration, the propulsion system, and the use of the aerodynamics is presented. To assess the STOL performance of the airplane, takeoff and landing distances and flight path capabilities were computed at various flap deflections and thrust levels. After evaluating these results in terms of desired STOL performance with required margins, basic takeoff and landing configurations were chosen.

Post, S. E.↗

Advanced technology for Space Shuttle Auxiliary Propellant Valves.

Propellant shutoff valves required for the operation of the pulse modulated gaseous hydrogen/gaseous oxygen rocket engines for the Space Shuttle Auxiliary Propulsion System are specified to operate for one million cycles over a ten-year period with zero maintenance, very fast response, very low leakage, and over a wide temperature range. Based on an analytical leakage and wear model, sealing configurations were conceived, sized, and developed. Two prototype valves featuring different components were designed, built, and evaluated for 100,000 cycles. Design concepts and test results are presented.

Wichmann, H.↗

Ion thruster system (8-cm) cyclic endurance test

This report describes the qualification test of an Engineering-Model 5-mN-thrust 8-cm-diameter mercury ion thruster which is representative of the Ion Auxiliary Propulsion System (IAPS) thrusters. Two of these thrusters are scheduled for future flight test. The cyclic endurance test described herein was a ground-based test performed in a vacuum facility with a liquid-nitrogen-cooled cryo-surface and a frozen mercury target. The Power Electronics Unit, Beam Shield, Gimal, and Propellant Tank that were used with the thruster in the endurance test are also similar to those of the IAPS. The IAPS thruster that will undergo the longest beam-on-time during the actual space test will be subjected to 7,055 hours of beam-on-time and 2,557 cycles during the flight test. The endurance test was successfully concluded when the mercury in the IAPS Propellant Tank was consumed. At that time, 8,471 hours of beam-on-time and 599 cycles had been accumulated. Subsequent post-test-evaluation operations were performed (without breaking vacuum) which extended the test values to 652 cycles and 9,489 hours of beam-on-time. The Power Electronic Unit (PEU) and thruster were in the same vacuum chamber throughout the test. The PEU accumulated 10,268 hr of test time with high voltage applied to the operating thruster or dummy load.

Dulgeroff, C. R.↗