Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “engineering process”

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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Flux REaction TArget Prioritization (Flux RETAP) v1

Metabolic engineering is evolving rapidly as a result of new advances in synthetic biology and automation, as well as the irruption of machine learning (ML). ML has been shown to provide the predictive power synthetic biology lacked and needed, and to be able to effectively guide the metabolic engineering process. However, current technical limitations prevent the independent application of ML approaches to metabolic engineering without the use of previous biological knowledge in the form of a prioritized list of desirable engineering targets. Here, we present FluxRETAP, a simple and computationally inexpensive method that leverages the prior mechanistic knowledge embedded in genome-scale metabolic models (GSMs) for suggesting targets for genetic overexpression, downregulation or deletion, with the final goal of increasing metabolite production. FluxRETAP captured 100% of reaction targets experimentally verified to improve Escherichia coli isoprenol production in the literature accessible to us, 50% of targets that experimentally improved taxadiene production in E. coli and ~60% of genetic targets from a verified minimal constrained cut-set in Pseudomonas putida while providing additional high priority targets that could be tested. Overall, FluxRETAP is an efficient algorithm for identifying a prioritized list of testable genetic and reaction targets which can also be utilized in ML pipelines.

Czajka, Jeffrey [Battelle Memorial Institute, Paci↗
NASA NTRS1985

The use of analogs in the innovation process - A software engineering protocol analysis

A human information processing account of how experienced practitioners utilize analogs in the innovation process is presented. The protocols of several practitioners are collected and analyzed. The problem behavior graphs, knowledge elements utilized, and operator elements applied are described, and a descriptive model of the innovation process is assembled. Implications for a production system, deviations from other models of the innovation process, and extensions to other models of the analogy procedure are explored.

Silverman, B. G.↗
NASA NTRS2022

Development of an Accepted Medical Condition List for Exploration Medical Capability Scoping

Future NASA human spaceflight programs are on the verge of moving beyond Low Earth Orbit (LEO) to implement missions in lunar space and ultimately Mars. The mission constraints for these types of missions are expected to be progressively challenging for integration of Human Systems requirements into the vehicle and mission architectures. Mass and volume allocations are expected to become increasingly restrictive at the same time that mission realities will drive an increasing need for crew self-sufficiency in the maintenance and repair of both vehicle systems and human systems. To meet these challenges, a systematic, traceable, and repeatable approach to identifying, defining, and prioritizing medical capabilities is required. To provide a systematic and repeatable approach to defining and prioritizing clinical capabilities for spaceflight medicine, a clear process is required for delivering a list of prioritized medical capabilities to the Systems Engineering process that will delineate the mass, power, volume, and similar needs and the trade space analysis for a given space vehicle and mission architecture.

Rebecca Blue↗
DOE OSTI2013

IN-LINE CHEMICAL SENSOR DEPLOYMENT IN A TRITIUM PLANT

The Savannah River Tritium Plant (TP) relies on well understood but aging sensor technology for process gas analysis. Though new sensor technologies have been brought to various readiness levels, the TP has been reluctant to install technologies that have not been tested in tritium service. This gap between sensor technology development and incorporating new technologies into practical applications demonstrates fundamental challenges that exist when transitioning from status quo to state-of-the-art in an extreme environment such as a tritium plant. These challenges stem from three root obstacles: 1) The need for a comprehensive assessment of process sensing needs and requirements; 2) The lack of a pick-list of process-compatible sensor technologies; and 3) The need to test technologies in a tritium-contaminated process environment without risking production. At Savannah River, these issues are being addressed in a two phase project. In the first phase, TP sensing requirements were determined by a team of process experts. Meanwhile, Savannah River National Laboratory sensor experts identified candidate technologies and related them to the TP processing requirements. The resulting roadmap links the candidate technologies to actual plant needs. To provide accurate assessments of how a candidate sensor technology would perform in a contaminated process environment, an instrument demonstration station was established within a TP glove box. This station was fabricated to TP process requirements and designed to handle high activity samples. The combination of roadmap and demonstration station provides the following assets: Creates a partnership between the process engineers and researchers for sensor selection, maturation, and insertion, Selects the right sensors for process conditions Provides a means for safely inserting new sensor technology into the process without risking production, and Provides a means to evaluate off normal occurrences where and when they occur. This paper discusses the process to identify and demonstrate new sensor technologies for the Savannah River TP.

07 ISOTOPE AND RADIATION SOURCES↗
NASA NTRS1940

Resonance vibrations in intake and exhaust pipes of in-line engines III : the inlet process of a four-stroke-cycle engine

Using a previously developed method, the boundary process of four-stroke-cycle engines are set up. The results deviate considerably from those obtained under the assumption that the velocity fluctuation is proportional to the cylinder piston motion. The deviation is less at the position of resonance frequencies. By the method developed, the effect of the resonance vibrations on the volumetric efficiency can be demonstrated.

Lutz, O↗
DOE OSTI2026

Enhanced accuracy through ensembling of randomly initialized auto-regressive models for dynamical systems

Computational mechanics simulations using traditional finite element methods (FEM) require prohibitively expensive computational resources for real-time engineering applications, design optimization, and digital twin implementations. While machine learning (ML) surrogate models offer significant computational speedups, autoregressive ML models for time-dependent mechanical systems suffer from error accumulation that compromises long-term prediction reliability - a critical concern for engineering applications where accuracy over extended time horizons is essential for safety and performance assessments. Here, we propose a deep ensemble framework specifically designed to address this challenge in computational mechanics applications, where multiple ML surrogate models with random weight initializations are trained in parallel and their predictions aggregated during inference. This approach leverages statistical diversity to maximize information gain from a fixed set of training data and to mitigate error propagation, while maintaining the computational efficiency that makes ML surrogates attractive for engineering practice. We validate the framework on three representative problems spanning critical areas of computational mechanics: stress field evolution in heterogeneous microstructures under complex loading (relevant to advanced materials design and composite analysis), planetary-scale shallow water dynamics (applicable to environmental and geotechnical engineering), and Gray-Scott reaction-diffusion systems (relevant to mass transport and chemical process engineering). Across all test cases, the ensemble approach demonstrates consistent error reduction of 15-33% compared to individual models. The codes for this work are available on GitHub (https://github.com/Graham-Brady-Research-Group/AutoregressiveEnsemble_SpatioTemporal_Evolution).

autoregressive prediction↗
DOE OSTI2014

Fundamental Aspects of Selective Melting Additive Manufacturing Processes

Certain details of the additive manufacturing process known as selective laser melting (SLM) affect the performance of the final metal part. To unleash the full potential of SLM it is crucial that the process engineer in the field receives guidance about how to select values for a multitude of process variables employed in the building process. These include, for example, the type of powder (e.g., size distribution, shape, type of alloy), orientation of the build axis, the beam scan rate, the beam power density, the scan pattern and scan rate. The science-based selection of these settings con- stitutes an intrinsically challenging multi-physics problem involving heating and melting a metal alloy, reactive, dynamic wetting followed by re-solidification. In addition, inherent to the process is its considerable variability that stems from the powder packing. Each time a limited number of powder particles are placed, the stacking is intrinsically different from the previous, possessing a different geometry, and having a different set of contact areas with the surrounding particles. As a result, even if all other process parameters (scan rate, etc) are exactly the same, the shape and contact geometry and area of the final melt pool will be unique to that particular configuration. This report identifies the most important issues facing SLM, discusses the fundamental physics associated with it and points out how modeling can support the additive manufacturing efforts.

36 MATERIALS SCIENCE↗
DOE OSTI2018

The Strategic Value of Human Factors Engineering in Control Room Modernization

Control room modernization is one of the most challenging and complex upgrade projects that a nuclear power plant can undertake. It can have almost as big an impact on operations as, for example, turbine replacement. The challenges of migrating an analog control system to a distributed control system are already well known and a number of nuclear utilities have embarked upon various levels of effort to upgrade some of the systems in the control room. When planning for control room upgrades, plants have to deal with a multitude of engineering, operational, and regulatory impacts. This will inevitably include several human factors considerations, such as workstation ergonomics, viewing angles, lighting, seating, new interaction modalities, new communication requirements, and new concepts of operation. In helping nuclear power utilities to deal with these challenges, the United States Department of Energy researchers located at Idaho National Laboratory (INL) have developed research-based human factors design and evaluation methods to be used in the development of end-state concepts for modernized control rooms and to manage the various phases of the upgrade life cycle. The methodology includes interactive sessions with operators in INL’s Human System Simulation Laboratory, three-dimensional modeling to visualize control board changes and operator-system interaction, and development of human-system prototypes to evaluate various aspects of proposed modifications. This methodology has been applied at a number of U.S. nuclear power plants where modernization projects are underway, including Exelon’s Braidwood and Byron plants, and Arizona Public Service's Palo Verde plant. It was demonstrated that including this methodology in the plant’s engineering process helps to ensure an integrated and cohesive outcome that is consistent with human factors engineering principles and provide substantial improvement in operator performance.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1995

NASA Systems Engineering Handbook

This handbook brings the fundamental concepts and techniques of systems engineering to NASA personnel in a way that recognizes the nature of NASA systems and environment. It is intended to accompany formal NASA training courses on systems engineering and project management when appropriate, and is designed to be a top-level overview. The concepts were drawn from NASA field center handbooks, NMI's/NHB's, the work of the NASA-wide Systems Engineering Working Group and the Systems Engineering Process Improvement Task team, several non-NASA textbooks and guides, and material from independent systems engineering courses taught to NASA personnel. Five core chapters cover systems engineering fundamentals, the NASA Project Cycle, management issues in systems engineering, systems analysis and modeling, and specialty engineering integration. It is not intended as a directive. Superseded by: NASA/SP-2007-6105 Rev 1 (20080008301).

Shishko, Robert↗
NASA NTRS2012

The Montana ALE (Autonomous Lunar Excavator) Systems Engineering Report

On May 2 1-26, 20 12, the third annual NASA Lunabotics Mining Competition will be held at the Kennedy Space Center in Florida. This event brings together student teams from universities around the world to compete in an engineering challenge. Each team must design, build and operate a robotic excavator that can collect artificial lunar soil and deposit it at a target location. Montana State University, Bozeman, is one of the institutions selected to field a team this year. This paper will summarize the goals of MSU's lunar excavator project, known as the Autonomous Lunar Explorer (ALE), along with the engineering process that the MSU team is using to fulfill these goals, according to NASA's systems engineering guidelines.

Lars Osborne↗
NASA NTRS2016

EDEN: A Novel Approach to Plant Growth in Space

The USU XHAB Eden Team has enjoyed the opportunity to participate in NASA’s X­HAB Challenge. Our project involved constructing a prototype to further investigate the complexities of growing plants in microgravity environments. Attached is the team’s report which covers the research and design of our prototype. Included is a summary of our design, drawings and schematics with an as built status, engineering process documents, and all other documentation necessary to satisfy the requirements of Utah State University’s Engineering Design Course (MAE 4810).

Timothy Taylor↗
DOE OSTI2014

Scale-Up Information for Gas-Phase Ammonia Treatment of Uranium in the Vadose Zone at the Hanford Site Central Plateau

Uranium is present in the vadose zone at the Hanford Central Plateau and is of concern for protection of groundwater. The Deep Vadose Zone Treatability Test Plan for the Hanford Central Plateau identified gas-phase treatment and geochemical manipulation as potentially effective treatment approaches for uranium and technetium in the Hanford Central Plateau vadose zone. Based on laboratory evaluation, use of ammonia vapor was selected as the most promising uranium treatment candidate for further development and field testing. While laboratory tests have shown that ammonia treatment effectively reduces the mobility of uranium, additional information is needed to enable deployment of this technology for remediation. Of importance for field applications are aspects of the technology associated with effective distribution of ammonia to a targeted treatment zone, understanding the fate of injected ammonia and its impact on subsurface conditions, and identifying effective monitoring approaches. In addition, information is needed to select equipment and operational parameters for a field design. As part of development efforts for the ammonia technology for remediation of vadose zone uranium contamination, field scale-up issues were identified and have been addressed through a series of laboratory and modeling efforts. This report presents a conceptual description for field application of the ammonia treatment process, engineering calculations to support treatment design, ammonia transport information, field application monitoring approaches, and a discussion of processes affecting the fate of ammonia in the subsurface. The report compiles this information from previous publications and from recent research and development activities. The intent of this report is to provide technical information about these scale-up elements to support the design and operation of a field test for the ammonia treatment technology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2000

Session on High Speed Civil Transport Design Capability Using MDO and High Performance Computing

Since the inception of CAS in 1992, NASA Langley has been conducting research into applying multidisciplinary optimization (MDO) and high performance computing toward reducing aircraft design cycle time. The focus of this research has been the development of a series of computational frameworks and associated applications that increased in capability, complexity, and performance over time. The culmination of this effort is an automated high-fidelity analysis capability for a high speed civil transport (HSCT) vehicle installed on a network of heterogeneous computers with a computational framework built using Common Object Request Broker Architecture (CORBA) and Java. The main focus of the research in the early years was the development of the Framework for Interdisciplinary Design Optimization (FIDO) and associated HSCT applications. While the FIDO effort was eventually halted, work continued on HSCT applications of ever increasing complexity. The current application, HSCT4.0, employs high fidelity CFD and FEM analysis codes. For each analysis cycle, the vehicle geometry and computational grids are updated using new values for design variables. Processes for aeroelastic trim, loads convergence, displacement transfer, stress and buckling, and performance have been developed. In all, a total of 70 processes are integrated in the analysis framework. Many of the key processes include automatic differentiation capabilities to provide sensitivity information that can be used in optimization. A software engineering process was developed to manage this large project. Defining the interactions among 70 processes turned out to be an enormous, but essential, task. A formal requirements document was prepared that defined data flow among processes and subprocesses. A design document was then developed that translated the requirements into actual software design. A validation program was defined and implemented to ensure that codes integrated into the framework produced the same results as their standalone counterparts. Finally, a Commercial Off the Shelf (COTS) configuration management system was used to organize the software development. A computational environment, CJOPT, based on the Common Object Request Broker Architecture, CORBA, and the Java programming language has been developed as a framework for multidisciplinary analysis and Optimization. The environment exploits the parallelisms inherent in the application and distributes the constituent disciplines on machines best suited to their needs. In CJOpt, a discipline code is "wrapped" as an object. An interface to the object identifies the functionality (services) provided by the discipline, defined in Interface Definition Language (IDL) and implemented using Java. The results of using the HSCT4.0 capability are described. A summary of lessons learned is also presented. The use of some of the processes, codes, and techniques by industry are highlighted. The application of the methodology developed in this research to other aircraft are described. Finally, we show how the experience gained is being applied to entirely new vehicles, such as the Reusable Space Transportation System. Additional information is contained in the original.

Rehder, Joe↗
DOE OSTI2015

Development of a Novel Gas Pressurized Stripping Process-Based Technology for CO₂ Capture from Post-Combustion Flue Gases

A novel Gas Pressurized Stripping (GPS) post-combustion carbon capture (PCC) process has been developed by Carbon Capture Scientific, LLC, CONSOL Energy Inc., Nexant Inc., and Western Kentucky University in this bench-scale project. The GPS-based process presents a unique approach that uses a gas pressurized technology for CO₂ stripping at an elevated pressure to overcome the energy use and other disadvantages associated with the benchmark monoethanolamine (MEA) process. The project was aimed at performing laboratory- and bench-scale experiments to prove its technical feasibility and generate process engineering and scale-up data, and conducting a techno-economic analysis (TEA) to demonstrate its energy use and cost competitiveness over the MEA process. To meet project goals and objectives, a combination of experimental work, process simulation, and technical and economic analysis studies were applied. The project conducted individual unit lab-scale tests for major process components, including a first absorption column, a GPS column, a second absorption column, and a flasher. Computer simulations were carried out to study the GPS column behavior under different operating conditions, to optimize the column design and operation, and to optimize the GPS process for an existing and a new power plant. The vapor-liquid equilibrium data under high loading and high temperature for the selected amines were also measured. The thermal and oxidative stability of the selected solvents were also tested experimentally and presented. A bench-scale column-based unit capable of achieving at least 90% CO₂ capture from a nominal 500 SLPM coal-derived flue gas slipstream was designed and built. This integrated, continuous, skid-mounted GPS system was tested using real flue gas from a coal-fired boiler at the National Carbon Capture Center (NCCC). The technical challenges of the GPS technology in stability, corrosion, and foaming of selected solvents, and environmental, health and safety risks have been addressed through experimental tests, consultation with vendors and engineering analysis. Multiple rounds of TEA were performed to improve the GPS-based PCC process design and operation, and to compare the energy use and cost performance of a nominal 550-MWe supercritical pulverized coal (PC) plant among the DOE/NETL report Case 11 (the PC plant without CO₂ capture), the DOE/NETL report Case 12 (the PC plant with benchmark MEA-based PCC), and the PC plant using GPS-based PCC. The results reveal that the net power produced in the PC plant with GPS-based PCC is 647 MWe, greater than that of the Case 12 (550 MWe). The 20-year LCOE for the PC plant with GPS-based PCC is 97.4 mills/kWh, or 152% of that of the Case 11, which is also 23% less than that of the Case 12. These results demonstrate that the GPS-based PCC process is energy-efficient and cost-effective compared with the benchmark MEA process.

Chen, Shiaoguo↗
DOE OSTI2020

Stochasticity in microbiology: managing unpredictability to reach the Sustainable Development Goals

Pure (single) cultures of microorganisms and mixed microbial communities (microbiomes) have been important for centuries in providing renewable energy, clean water and food products to human society and will continue to play a crucial role to pursue the Sustainable Development Goals. To use microorganisms effectively, microbial engineered processes require adequate control. Microbial communities are shaped by manageable deterministic processes, but also by stochastic processes, which can promote unforeseeable variations and adaptations. Here, we highlight the impact of stochasticity in single culture and microbiome engineering. First, we discuss the concepts and mechanisms of stochasticity in relation to microbial ecology of single cultures and microbiomes. Second, we discuss the consequences of stochasticity in relation to process performance and human health, which are reflected in key disadvantages and important opportunities. Third, we propose a suitable decision tool to deal with stochasticity in which monitoring of stochasticity and setting the boundaries of stochasticity by regulators are central aspects. Stochasticity may give rise to some risks, such as the presence of pathogens in microbiomes. We argue here that by taking the necessary precautions and through clever monitoring and interpretation, these risks can be mitigated.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2011

Space Transportation System Liftoff Debris Mitigation Process Overview

Liftoff debris is a top risk to the Space Shuttle Vehicle. To manage the Liftoff debris risk, the Space Shuttle Program created a team with in the Propulsion Systems Engineering & Integration Office. The Shutt le Liftoff Debris Team harnesses the Systems Engineering process to i dentify, assess, mitigate, and communicate the Liftoff debris risk. T he Liftoff Debris Team leverages off the technical knowledge and expe rtise of engineering groups across multiple NASA centers to integrate total system solutions. These solutions connect the hardware and ana lyses to identify and characterize debris sources and zones contribut ing to the Liftoff debris risk. The solutions incorporate analyses sp anning: the definition and modeling of natural and induced environmen ts; material characterizations; statistical trending analyses, imager y based trajectory analyses; debris transport analyses, and risk asse ssments. The verification and validation of these analyses are bound by conservative assumptions and anchored by testing and flight data. The Liftoff debris risk mitigation is managed through vigilant collab orative work between the Liftoff Debris Team and Launch Pad Operation s personnel and through the management of requirements, interfaces, r isk documentation, configurations, and technical data. Furthermore, o n day of launch, decision analysis is used to apply the wealth of ana lyses to case specific identified risks. This presentation describes how the Liftoff Debris Team applies Systems Engineering in their proce sses to mitigate risk and improve the safety of the Space Shuttle Veh icle.

Mitchell, Michael↗
DOE OSTI2020

Preliminary Design Process for Networked Microgrids

Changes in economic, technology, and environmental policies are resulting in a re-evaluation of the dependence on large central generation facilities and their associated transmission networks. Emerging concepts of smart communities/cities are examining the potential to leverage cleaner sources of generation, and the potential to integrate electricity generation with other municipal functions. When grid-connected, these generation assets can supplement the existing interconnections with the bulk transmission system, and in the event of an extreme event, they can provide power via networks of microgrids. While the design process for a single stand-alone microgrid is relatively well understood, the process of designing the infrastructure for networked microgrid operations has not been well studied. Because of the wide range of potential operational goals for microgrids, it is typical to follow the engineering process of developing an initial conceptual design, a preliminary design, a detailed design, and then a final as-built design. The conceptual design is typically completed without detailed engineering analysis, and the preliminary design is the first stage that requires it. This paper presents a process for developing the preliminary design for networked microgrids, which can then be used as a basis for the final as-built design.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Global optimization of multicomponent distillation configurations: Global minimization of total cost for multicomponent mixture separations

We introduce a global optimization framework for determining the minimum cost required to distill any ideal or near-ideal multicomponent mixture into its individual constituents using a sequence of columns. This new framework extends the Global Minimization Algorithm (GMA) previously introduced by Nallasivam et al. (2016); and we refer to the new framework as the Global Minimization Algorithm for Cost (GMAC). GMAC guarantees global optimality by formulating a nonlinear program (NLP) for each and every distillation configuration in the search space and solving it using global optimization solvers. In conclusion, the case study presented in this work not only demonstrates the need for developing such an algorithm, but also shows the flexibility and effectiveness of GMAC, which enables process engineers to design and retrofit energy efficient and cost-effective distillation configurations.

42 ENGINEERING↗