Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Process Engineering”

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 1,765 records · Page 98
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Modular Subsurface Sensors and Integrated Software for Advanced Subsurface Characterization and Monitoring using Unoccupied Vehicles

The advent and subsequent proliferation of autonomous airborne, waterborne, and groundbased vehicles (i.e., “drones”) promises to broadly transform the geosciences and associated industries, including fossil energy exploration and development, mineral resource exploration and development, water-resource management, and environmental remediation. For geophysical characterization and monitoring, the prospect of programming highly repeatable and low-cost drone missions for subsurface imaging will allow for deployments in hazardous and previously inaccessible areas. Coupled with autonomous workflows for data processing, management, and visualization, drone-based geophysical characterization and monitoring will enable unprecedented, real-time insight into diverse subsurface properties and processes of scientific and engineering importance. Toward this end, the objectives of this Lab Directed Research and Development (LDRD) project were to develop new (1) instrumentation for dronebased electromagnetic induction (EMI) geophysical imaging, including separated transmitter and receivers and associated electronics, (2) software for real-time data telemetry, processing, management, and visualization. Although EMI has been previously deployed using unoccupied aerial systems (UASs), these applications failed to capitalize on the game-changing capabilities of drone platforms. Whereas drone-based data acquisition allows for collection of rich, three-dimensional (3D) multi-offset/multi-angle configurations between transmitters and receivers, past efforts have relied on conventional instrumentation that was designed for ground-based data collection with the transmitter and a single receiver housed in the same unit; nor did these previous applications demonstrate real-time delivery of results to support rapid management decisions in the field. In this 1-year project, we (1) designed and constructed new lightweight independent transmitter and receiver antenna platforms that communicate with a laptop computer; (2) developed software to control data acquisition, manage/transfer data, and visualize data as its collected; and (3) demonstrated the operation of the new hardware and software systems in a ground-based field test. Our work entails major technological advances for EMI and established a foundation on which to build a new drone-based, real-time geophysical EMI imaging capability to support diverse challenges facing the nation.

47 OTHER INSTRUMENTATION↗
NASA NTRS1990

The composite load spectra project

Probabilistic methods and generic load models capable of simulating the load spectra that are induced in space propulsion system components are being developed. Four engine component types (the transfer ducts, the turbine blades, the liquid oxygen posts and the turbopump oxidizer discharge duct) were selected as representative hardware examples. The composite load spectra that simulate the probabilistic loads for these components are typically used as the input loads for a probabilistic structural analysis. The knowledge-based system approach used for the composite load spectra project provides an ideal environment for incremental development. The intelligent database paradigm employed in developing the expert system provides a smooth coupling between the numerical processing and the symbolic (information) processing. Large volumes of engine load information and engineering data are stored in database format and managed by a database management system. Numerical procedures for probabilistic load simulation and database management functions are controlled by rule modules. Rules were hard-wired as decision trees into rule modules to perform process control tasks. There are modules to retrieve load information and models. There are modules to select loads and models to carry out quick load calculations or make an input file for full duty-cycle time dependent load simulation. The composite load spectra load expert system implemented today is capable of performing intelligent rocket engine load spectra simulation. Further development of the expert system will provide tutorial capability for users to learn from it.

Newell, J. F.↗
NASA NTRS2015

A Systems Engineering Approach to Quality Assurance for Aerospace Testing

On the surface, it appears that AS91001 has little to say about how to apply a Quality Management System (QMS) to major aerospace test programs (or even smaller ones). It also appears that there is little in the quality engineering Body of Knowledge (BOK)2 that applies to testing, unless it is nondestructive examination (NDE), or some type of lab or bench testing associated with the manufacturing process. However, if one examines: a) how the systems engineering (SE) processes are implemented throughout a test program; and b) how these SE processes can be mapped to the requirements of AS9100, a number of areas for involvement of the quality professional are revealed. What often happens is that quality assurance during a test program is limited to inspections of the test article; what could be considered a manufacturing al fresco approach. This limits the quality professional and is a disservice to the programs and projects, since there are a number of ways that quality can enhance critical processes, and support efforts to improve risk reduction, efficiency and effectiveness.

Shepherd, Christena C.↗
DOE OSTI2021

A Component-Sizing Methodology for a Hybrid Electric Vehicle Using an Optimization Algorithm

Many leading companies in the automotive industry have been putting tremendous effort into developing new powertrains and technologies to make their products more energy efficient. Evaluating the fuel economy benefit of a new technology in specific powertrain systems is straightforward; and, in an early concept phase, obtaining a projection of energy efficiency benefits from new technologies is extremely useful. However, when carmakers consider new technology or powertrain configurations, they must deal with a trade-off problem involving factors such as energy efficiency and performance, because of the complexities of sizing a vehicle’s powertrain components, which directly affect its energy efficiency and dynamic performance. As powertrains of modern vehicles become more complicated, even more effort is required to design the size of each component. This study presents a component-sizing process based on the forward-looking vehicle simulator “Autonomie” and the optimization algorithm “POUNDERS”; the supervisory control strategy based on Pontryagin’s Minimum Principle (PMP) assures sufficient computational system efficiency. We tested the process by applying it to a single power-split hybrid electric vehicle to determine optimal values of gear ratios and each component size, where we defined the optimization problem as minimizing energy consumption when the vehicle’s dynamic performance is given as a performance constraint. The suggested sizing process will be helpful in determining optimal component sizes for vehicle powertrain to maximize fuel efficiency while dynamic performance is satisfied. Indeed, this process does not require the engineer’s intuition or rules based on heuristics required in the rule-based process.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Literature Review of Documented Persistent Secondary Uranium Sources at DOE LM Sites

The U.S. Department of Energy Office of Legacy Management (LM) has the responsibility to protect human health and the environment at 101 legacy uranium sites across the nation by implementing long-term surveillance and maintenance requirements. Included in these responsibilities is to provide for the safe and environmentally sound disposal, long-term stabilization, and control of uranium mill tailings in a manner that minimizes or eliminates radiation health hazards to the public at 21 Uranium Mill Tailings Radiation Control Act (UMTRCA) Title I sites; 6 UMTRCA Title II sites; and 9 Comprehensive Environmental Response, Compensation, and Liability Act/Resource Conservation and Recovery Act sites. These sites are former uranium mills (processing sites), or sites with wastes from processing sites encapsulated in engineered disposal cells (disposal sites), or sites where components of atomic weapons were manufactured. During site characterization, groundwater contamination was often discovered and evaluated or modeled for future movement with the inclusion of uranium sorption in the groundwater plume. Much of this original work did identify uranium processing wastes as the original contaminant source. However, more recent work has identified the existence and influence of persistent secondary uranium sources that may prevent uranium in groundwater from attenuating as quickly as initial evaluations or modeling indicated. By understanding these processes, better decisions can be made to choose the appropriate remediation and closure strategies, identify long-term surveillance and maintenance activities, and more accurately estimate life-cycle costs. The purpose of this report is to summarize the literature available on documented persistence secondary uranium sources at LM sites as part of the Applied Studies and Technology Persistent Secondary Contaminant Sources Project.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2007

Robust Low-Cost Cathode for Commercial Applications

Under funding from the NASA Commercial Technology Office, a cathode assembly was designed, developed, fabricated, and tested for use in plasma sources for ground-based materials processing applications. The cathode development activity relied on the large prior NASA investment and successful development of high-current, high-efficiency, long-life hollow cathodes for use on the International Space Station Plasma Contactor System. The hollow cathode was designed and fabricated based on known engineering criteria and manufacturing processes for compatibility with the requirements of the plasma source. The transfer of NASA GRC-developed hollow cathode technology for use as an electron emitter in the commercial plasma source is anticipated to yield a significant increase in process control, while eliminating the present issues of electron emitter lifetime and contamination.

Patterson, Michael J.↗
NASA NTRS2014

Possible Mechanisms for Turbofan Engine Ice Crystal Icing at High Altitude

A thermodynamic model is presented to describe possible mechanisms of ice formation on unheated surfaces inside a turbofan engine compression system from fully glaciated ice crystal clouds often formed at high altitude near deep convective weather systems. It is shown from the analysis that generally there could be two distinct types of ice formation: (1) when the "surface freezing fraction" is in the range of 0 to 1, dominated by the freezing of water melt from fully or partially melted ice crystals, the ice structure is formed from accretion with strong adhesion to the surface, and (2) when the "surface melting fraction" is the range of 0 to 1, dominated by the further melting of ice crystals, the ice structure is formed from accumulation of un-melted ice crystals with relatively weak bonding to the surface. The model captures important qualitative trends of the fundamental ice-crystal icing phenomenon reported earlier1,2 from the research collaboration work by NASA and the National Research Council (NRC) of Canada. Further, preliminary analysis of test data from the 2013 full scale turbofan engine ice crystal icing test3 conducted in the NASA Glenn Propulsion Systems Laboratory (PSL) has also suggested that (1) both types of ice formation occurred during the test, and (2) the model has captured some important qualitative trend of turning on (or off) the ice crystal ice formation process in the tested engine low pressure compressor (LPC) targeted area under different icing conditions that ultimately would lead to (or suppress) an engine core roll back (RB) event.

Crystal Icing↗
DOE OSTI2023

Building a Computational and Experimental Rapid Response Pipeline to Counter the Coronavirus Disease 2019 Outbreak and Emerging Biothreats

The COVID-19 pandemic underscored the promise of monoclonal antibody-based prophylactic and therapeutic drugs, especially where protective candidates can be rapidly identified or developed for emerging biothreats and escape variants. Current cutting-edge technologies for this purpose still rely on pathogen-exposed convalescent volunteers and a large screening effort to find a proverbial needle in a haystack. Computational design of protective antibodies based on pre-existing templates skips those requirements and allows for greater control over the breadth and target epitope, while also co-optimizing for potency and developability or other biophysical characteristics. We approached this problem by building and expanding an in vitro experimental rapid antibody production and characterization pipeline to support development of an autonomous, closed loop, active learning software system based on structural simulation and ground truth experimental data to design and evaluate antibody antigen interactions. Starting from early in the pandemic, we targeted SARS-CoV-2, the causative agent of COVID-19, by re-purposing neutralizing antibodies against SARS-CoV-1 that had been identified in the wake of that outbreak in the early 2000’s. We successfully re-targeted three different anti-SARS-CoV-1 antibodies to neutralize SARS-CoV-2 in vitro, where the antibodies were generated externally and tested through conventional binding and neutralization assays internally or with collaborators. As antibodies were identified from the blood of humans infected with SARS-CoV-2, we shifted to collaborate with academic partners to develop improved versions of their human-derived antibodies. This work reached its most important stage in rapid response to the emergence of the Omicron variant of concern (VOC) in late 2021. In a matter of weeks, enabled by on demand innovation to our screening pipeline, we computationally designed and experimentally characterized derivative antibodies of COV2-2130, one of two antibodies from Vanderbilt that form the basis of the AstraZeneca Evusheld prophylactic drug product. This drug product suffers a serious loss of efficacy against Omicron BA.1 and BA.1.1, the first Omicron strains. Due to tight integration of computational design and experimental evaluation, we were able to identify a pair of designs with potent neutralization of the main targets Omicron BA.1 and BA.1.1; but also the earlier Delta variant, and subsequent Omicron strains including BA.2, BA.4, BA.5, and BA.2.75, demonstrating that our multi-target design process can, by its nature, produce robust antibody designs that strictly improve over the parental antibody. These results, recognized by a 2022 Director’s Science and Technology award, have enabled the follow-on GUIDE program, to commence in FY23. While earlier design campaigns were substantially outsourced, we have engineered better and faster processes internally to better compliment, calibrate, and speed computational designs. As part of the follow-on GUIDE program, we will stand up a rapid and high-throughput antibody production and characterization facility staffed with the expertise and capabilities to foster our current collaboration across PLS and ENG as well as other partnerships toward computational design of biologics.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1984

STAEBL: Structural tailoring of engine blades, phase 2

The Structural Tailoring of Engine Blades (STAEBL) program was initiated at NASA Lewis Research Center in 1980 to introduce optimal structural tailoring into the design process for aircraft gas turbine engine blades. The standard procedure for blade design is highly iterative with the engineer directly providing most of the decisions that control the design process. The goal of the STAEBL program has been to develop an automated approach to generate structurally optimal blade designs. The program has evolved as a three-phase effort with the developmental work being performed contractually by Pratt & Whitney Aircraft. Phase 1 was intended as a proof of concept in which two fan blades were structurally tailored to meet a full set of structural design constraints while minimizing DOC+I (direct operating cost plus interest) for a representative aircraft. This phase was successfully completed and was reported in reference 1 and 2. Phase 2 has recently been completed and is the basis for this discussion. During this phase, three tasks were accomplished: (1) a nonproprietary structural tailoring computer code was developed; (2) a dedicated approximate finite-element analysis was developed; and (3) an approximate large-deflection analysis was developed to assess local foreign object damage. Phase 3 is just beginning and is designed to incorporated aerodynamic analyses directly into the structural tailoring system in order to relax current geometric constraints.

Hirschbein, M. S.↗
DOE OSTI2020

Unconventional Catalytic Approaches to Ammonia Synthesis

Ammonia is a critically important industrial chemical and is largely responsible for sustaining the growing global population. To provide ammonia to underdeveloped regions and/or regions far from industrial production hubs, modular systems have been targeted and often involve unconventional production methodologies. These novel approaches for ammonia production can tap renewable resources at smaller scales located at the point of use, while decreasing the CO 2 footprint. Plasma-assisted catalysis and electrochemical ammonia synthesis have promise owing to their atmospheric pressure and low-temperature operation conditions and the ability to construct units at scales desired for modularization. Fundamental and applied studies are underway to assess these processes, although many unknowns remain. In this review, we discuss recent developments and opportunities for unconventional ammonia synthesis with a focus on plasma-stimulated systems.

42 ENGINEERING↗
NASA NTRS1992

An intelligent decomposition approach for efficient design of non-hierarchic systems

The design process associated with large engineering systems requires an initial decomposition of the complex systems into subsystem modules which are coupled through transference of output data. The implementation of such a decomposition approach assumes the ability exists to determine what subsystems and interactions exist and what order of execution will be imposed during the analysis process. Unfortunately, this is quite often an extremely complex task which may be beyond human ability to efficiently achieve. Further, in optimizing such a coupled system, it is essential to be able to determine which interactions figure prominently enough to significantly affect the accuracy of the optimal solution. The ability to determine 'weak' versus 'strong' coupling strengths would aid the designer in deciding which couplings could be permanently removed from consideration or which could be temporarily suspended so as to achieve computational savings with minimal loss in solution accuracy. An approach that uses normalized sensitivities to quantify coupling strengths is presented. The approach is applied to a coupled system composed of analysis equations for verification purposes.

Bloebaum, Christina L.↗
NASA NTRS2016

Possible Mechanisms for Turbofan Engine Ice Crystal Icing at High Altitude

A thermodynamic model is presented to describe possible mechanisms of ice formation on unheated surfaces inside a turbofan engine compression system from fully glaciated ice crystal clouds often formed at high altitude near deep convective weather systems. It is shown from the analysis that generally there could be two distinct types of ice formation: (1) when the "surface freezing fraction" is in the range of 0 to 1, dominated by the freezing of water melt from fully or partially melted ice crystals, the ice structure is formed from accretion with strong adhesion to the surface, and (2) when the "surface melting fraction" is the range of 0 to 1, dominated by the further melting of ice crystals, the ice structure is formed from accumulation of un-melted ice crystals with relatively weak bonding to the surface. The model captures important qualitative trends of the fundamental ice-crystal icing phenomenon reported earlier (Refs. 1 and 2) from the research collaboration work by NASA and the National Research Council (NRC) of Canada. Further, preliminary analysis of test data from the 2013 full scale turbofan engine ice crystal icing test (Ref. 3) conducted in the NASA Glenn Propulsion Systems Laboratory (PSL) has also suggested that (1) both types of ice formation occurred during the test, and (2) the model has captured some important qualitative trend of turning on (or off) the ice crystal ice formation process in the tested engine low pressure compressor (LPC) targeted area under different icing conditions that ultimately would lead to (or suppress) an engine core roll back (RB) event.

Crystal Icing↗
DOE OSTI2021

A microscopic and crystallographic study of proton irradiated alloy 718

Solution annealing and age hardening are important processes for achieving good engineering and chemical properties of alloy 718. The composition of alloy 718 also plays an important role as it can affect both mechanical (γ”- and γ’-phase formation) and irradiation behaviors. Therefore, in this study five different sets of alloy 718 samples with two different chemical compositions were fabricated using different processing conditions and irradiated up to 4 dpa. Based on the effects of irradiation on the microstructural data of γ”- and γ’-phases, irradiation-induced dislocation statistics, and crystallographic data, it can be inferred that the samples processed at high solution annealing temperature (1093°C) behave better under irradiation compared to the samples processed at low solution annealing temperatures (945 and 1065°C).

36 MATERIALS SCIENCE↗
DOE OSTI2025

Mixed-Integer Linear Programming Formulation with Embedded Machine Learning Surrogates for the Design of Chemical Process Families

In previous work, we introduced process family design. The main idea is to design a platform of common elements, and, allowing us to capture additional cost savings, simultaneously design a family of processes, and reducing both engineering and deployment timelines. We formulate this as an optimization problem, specifically a nonlinear generalized disjunctive program (GDP). We have proposed two approaches for reformulating and solving this problem: one based on full-discretization of the design space and one that uses Machine Learning (ML) surrogates to replace the nonlinear process models. Using ML surrogates to predict required system costs and performance indicators allows us to reformulate the nonlinearities in the GDP generate an efficient MILP formulation. In this work, we apply the ML surrogate approach to two case studies. One case study involves designing a family of carbon capture systems to cover a set of different flue gas flow rates and inlet CO 2 concentrations, where we consider the absorber and stripper as common unit module types. The second case study focuses on a water-desalination process, where we design a family of these processes for a variety of salt concentrations and flow rates. In both of these case studies, we demonstrate a scalable optimization approach that enables the design of multiple processes simultaneously, reducing the time-to-market and overall costs by maximizing the cost savings due to both economies of scale and economies of numbers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Generalized Information Architecture for Managing Requirements in IBM's Rational DOORS® Application

When a requirements engineering effort fails to meet expectations, often times the requirements management tool is blamed. Working with numerous project teams at Sandia National Laboratories over the last fifteen years has shown us that the tool is rarely the culprit; usually it is the lack of a viable information architecture with well-designed processes to support requirements engineering. This document illustrates design concepts with rationale, as well as a proven information architecture to structure and manage information in support of requirements engineering activities for any size or type of project. This generalized information architecture is specific to IBM's Rational DOORS (Dynamic Object Oriented Requirements System) software application, which is the requirements management tool in Sandia's CEE (Common Engineering Environment). This generalized information architecture can be used as presented or as a foundation for designing a tailored information architecture for project-specific needs. It may also be tailored for another software tool.

Aragon, Kathryn Mary↗
NASA NTRS2020

Assisted Authoring of Model-Based Systems Engineering Documents

In systems engineering practices system design and analysis have historically been performed using a document-centric approach where stakeholders produce a number of documents that represent their views on a system under development. Given the ad-hoc, disparate, and informal nature of natural language documents, these views become quickly inconsistent. Rigor in engineering work is also lost in the transition from model based engineering design and analysis to engineering documents. Once the documents are delivered, the engineering portion of the work is disconnected. In the Open Model Based Engineering Environment (OpenMBEE), Cross-References (aka transclusions) synthesize data for engineering when the information is not simply hyperlinked, but referenced in place in a document, upgrading a document-based process with model-based engineering technology. Those Cross-References are nowadays partially created manually, putting a burden on the engineer who is authoring the document.This paper presents an approach which can assist the engineer by providing machine-generated suggestions for Cross-References using language processing, graph analysis, and clustering technologies on model data managed by the OpenMBEE infrastructure.

Gomes, Ivan↗
NASA NTRS2020

Toa Baja Disasters: Utilizing Open-Source Earth Observations to Inform the Toa Baja Municipality’s Flood Mitigation Efforts and Educate the Public

Toa Baja, located just west of San Juan in Puerto Rico, is known as “the underwater city” due to its propensity to flood. The city contains the mouth of the island’s longest river, Río de la Plata, which drains into the Atlantic Ocean on the northern edge of the municipality. Proximity to these major water features and the flat, low terrain contribute to the flood-prone nature of the area. During tropical storm events, such as Hurricane Maria in 2017, Toa Baja experienced inundation of up to 20 feet. Changes in the global climate system are causing more intense and frequent tropical storms, making places like Toa Baja subject to irreparable damage. This NASA DEVELOP project collaborated with the Municipio Autónomo de Toa Baja, ResilientSEE, and the Massachusetts Institute of Technology Urban Risk Lab to supplement recent 2018 Federal Emergency Management Agency Hydraulic Engineering Centers-River Analysis System flood maps, which designated 63% of the area as a flood plain. The analysis provides a high-resolution interpretation of flood susceptibility using a variety of factors that collectively influence the likelihood of flooding. Sentinel-1 C-Band Synthetic Aperture Radar (C-SAR) data processed with Google Earth Engine scripting identified historical inundation and was used for validation purposes. Socioeconomic factors were combined with the inundation layer producing a final risk output. These outputs will improve public understanding of exposure to flood risk in Toa Baja and provide scientific evidence for flood mitigation advocacy.

Disasters↗
NASA NTRS2020

Toa Baja Disasters: Utilizing Open-Source Earth Observations to Inform the Toa Baja Municipality’s Flood Mitigation Efforts and Educate the Public

Toa Baja, located just west of San Juan in Puerto Rico, is known as “the underwater city” due to its propensity to flood. The city contains the mouth of the island’s longest river, Río de la Plata, which drains into the Atlantic Ocean on the northern edge of the municipality. Proximity to these major water features and the flat, low terrain contribute to the flood-prone nature of the area. During tropical storm events, such as Hurricane Maria in 2017, Toa Baja experienced inundation of up to 20 feet. Changes in the global climate system are causing more intense and frequent tropical storms, making places like Toa Baja subject to irreparable damage. This NASA DEVELOP project collaborated with the Municipio Autonómo de Toa Baja, ResilientSEE, and the Massachusetts Institute of Technology Urban Risk Lab to supplement recent 2018 Federal Emergency Management Agency Hydraulic Engineering Centers-River Analysis System flood maps, which designated 63% of the area as a flood plain. The analysis provides a high-resolution interpretation of flood susceptibility using a variety of factors that collectively influence the likelihood of flooding. Sentinel-1 C-Band Synthetic Aperture Radar (C-SAR) data processed with Google Earth Engine scripting identified historical inundation and was used for validation purposes. Socioeconomic factors were combined with the inundation layer producing a final risk output. These outputs will improve public understanding of exposure to flood risk in Toa Baja and provide scientific evidence for flood mitigation advocacy.

Disasters↗