Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Process based assessment”

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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Printed Wiring Board Technology Infusion and Supplier Capability Overview

Risk based technology infusion is a deliberate and systematic process which defines the analysis and communication methodology by which new technology is applied and integrated into existing and new designs, identifies technology development needs based on trends analysis and facilitates the identification of shortfalls against performance objectives. This presentation at QLF 2018 provides the audience a snapshot of quality variations in printed wiring board quality, as assessed, using experiences in processing and risk analysis of PWB structural integrity coupons. The presentation will focus on printed wiring board quality metrics used, the relative type and number of non-conformances observed and trend analysis using statistical methods. Trend analysis shows the top five non-conformances observed across PWB suppliers, the root cause(s) behind these non-conformance and suggestions of mitigation plans. The trends will then be matched with the current state of the PWB supplier base and its challenges and opportunities. The presentation further discusses the methods being applied at GSFC for evaluating candidate printed wiring board technologies which promote the adoption of higher throughput and faster processing technology for GSFC missions.

PCB fabrication↗
DOE OSTI2023

Cost optimization of low-salt-rejection reverse osmosis

Low-salt-rejection reverse osmosis (LSRRO) is an emerging membrane-based desalination technology for concentrating brines with potentially lower energy consumption and cost than thermally driven processes. We assess the technoeconomic performance of LSRRO by using an optimization model that minimizes the levelized cost of water (LCOW). We develop detailed models for the RO module and other equipment using WaterTAP (Water treatment Technoeconomic Assessment Platform), an open-source simulation and optimization software for water treatment. We improve upon previous LSRRO cost optimization studies by optimizing the salt permeability for each stage, which has significant implications for technoeconomic performance. We present the cost-optimal design, operation, and performance for three cases: 35 g/L TDS feed at 70% recovery, 70 g/L at 55%, and 125 g/L at 35%. The cost-optimal LCOW and specific energy consumption (SEC) for these cases are 0.70, 1.89, and 7.41 $/m 3 and 3.9, 8.4, and 30.4 kWh/m 3 , respectively. For each case, we use sensitivity analyses to provide guidance on key factors that impact economic viability. We also present the cost-optimal LCOW and SEC for feed concentrations between 5 and 220 g/L TDS and recoveries between 30 and 90%. So, we compare LSRRO to other high-salinity desalination technologies and find that it may be cost-competitive below feed concentrations of 125 g/L.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Optimizing genomic prediction for complex traits via investigating multiple factors in switchgrass

Genomic prediction has accelerated breeding processes and provided mechanistic insights into the genetic bases of complex traits. To further optimize genomic prediction, we assess the impact of genome assemblies, genotyping approaches, variant types, allelic complexities, polyploidy levels, and population structures on the prediction of 20 complex traits in switchgrass (Panicum virgatum L.), a perennial biofuel feedstock. Surprisingly, short read-based genome assembly performs comparably to or even better than long read-based assembly. Due to higher gene coverage, exome capture and multi-allelic variants outperform genotyping-by-sequencing and bi-allelic variants, respectively. Tetraploid models show higher prediction accuracy than octoploid models for most traits, likely due to the greater genetic distances among tetraploids. Depending on the trait in question, different types of variants need to be integrated for optimal predictions. Furthermore, our study provides insights into the factors influencing genomic prediction outcomes, guiding best practices for future studies and for improving agronomic traits in switchgrass and other species through selective breeding.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1980

Materials processing threshold report. 1: Semiconductor crystals for infrared detectors

An extensive search was performed of the open literature pertaining to infrared detectors to determine what constitutes a good detector and in what way performance is limited by specific material properties. Interviews were conducted with a number of experts in the field to assess their perceptions of the state of the art and of the utility of zero-gravity processing. Based on this information base and on a review of NASA programs in crystal growth and infrared sensors, NASA program goals were reassessed and suggestions are presented as to possible joint and divergent efforts between NASA and DOD.

Sager, E. V.↗
NASA NTRS1982

The impact of distributed computing on education

In this paper, developments in digital computer technology since the early Fifties are reviewed briefly, and the parallelism which exists between these developments and developments in analysis and design procedures of structural engineering is identified. The recent trends in digital computer technology are examined in order to establish the fact that distributed processing is now an accepted philosophy for further developments. The impact of this on the analysis and design practices of structural engineering is assessed by first examining these practices from a data processing standpoint to identify the key operations and data bases, and then fitting them to the characteristics of distributed processing. The merits and drawbacks of the present philosophy in educating structural engineers are discussed and projections are made for the industry-academia relations in the distributed processing environment of structural analysis and design. An ongoing experiment of distributed computing in a university environment is described.

Utku, S.↗
NASA NTRS1982

Technical and economic assessment of processes for the production of butanol and acetone

This report represents a preliminary technical and economic evaluation of a process which produces mixed solvents (butaol/acetone/ethanol) via fermentation of sugars derived from renewable biomass resources. The objective is to assess the technology of producing butanol/acetone from biomass, and select a viable process capable of serving as a base case model for technical and economic analysis. It is anticipated that the base case process developed herein can then be used as the basis for subsequent studies concerning biomass conversion processes capable of producing a wide range of chemicals. The general criteria utilized in determining the design basis for the process are profit potential and non-renewable energy displacement potential. The feedstock chosen, aspen wood, was selected from a number of potential renewable biomass resources as the most readily available in the United States and for its relatively large potential for producing reducing sugars.

Source record↗
NASA NTRS2012

A Briefing on Metrics and Risks for Autonomous Decision-Making in Aerospace Applications

Significant technology advances will enable future aerospace systems to safely and reliably make decisions autonomously, or without human interaction. The decision-making may result in actions that enable an aircraft or spacecraft in an off-nominal state or with slightly degraded components to achieve mission performance and safety goals while reducing or avoiding damage to the aircraft or spacecraft. Some key technology enablers for autonomous decision-making include: a continuous state awareness through the maturation of the prognostics health management field, novel sensor development, and the considerable gains made in computation power and data processing bandwidth versus system size. Sophisticated algorithms and physics based models coupled with these technological advances allow reliable assessment of a system, subsystem, or components. Decisions that balance mission objectives and constraints with remaining useful life predictions can be made autonomously to maintain safety requirements, optimal performance, and ensure mission objectives. This autonomous approach to decision-making will come with new risks and benefits, some of which will be examined in this paper. To start, an account of previous work to categorize or quantify autonomy in aerospace systems will be presented. In addition, a survey of perceived risks in autonomous decision-making in the context of piloted aircraft and remotely piloted or completely autonomous unmanned autonomous systems (UAS) will be presented based on interviews that were conducted with individuals from industry, academia, and government.

Frost, Susan↗
NASA NTRS2016

Distributed Schemes for Integrated Arrival Departure Surface (IADS) Scheduling

The objective of the NRA is to investigate and develop integrated scheduling solutions for arrival, departure and surface operations. The option year briefing summarizes simulation-based analyses of the departure metering process to investigate strategic queue management strategies and their robustness to uncertainty, assess the impact of delaying departures at their gates on blocking the arrivals destined for the same gates, and evaluate the effects and benefits of relaxing current-day MIT constraints when ATD-2 is in operation.

ATD-2↗
NASA NTRS2019

Nasa Conjunction Assessment Risk Analysis Updated Requirements Architecture

The NASA Conjunction Assessment Risk Analysis (CARA) program has been performing routine on-orbit satellite conjunction risk analysis for unmanned NASA spacecraft since 2005, and has developed a robust operations procedure and set of recommended best practices for operational conjunction assessment. However, a number of recent developments in Space Situational Awareness and commercial space operations conduct, such as the immanent deployment of much more sensitive space sensing systems and the launching of much larger satellite constellations, have begun to challenge these standard collision risk parameters and calculations. In response CARA has pursued a multi-year evaluation initiative to re-examine risk assessment algorithms and techniques, to develop needed improvements, and to assemble analysis-based operational requirements. This paper gives an overview of the principal parts of the Conjunction Assessment (CA) risk assessment process used at CARA, outlines the technical challenges that each part presents, surveys the possible solutions, and then indicates which particular solution is being recommended for NASA.

Newman, Lauri K.↗
NASA NTRS2019

NASA Conjunction Assessment Risk Analysis (CARA) Updated Requirements Architecture

The NASA Conjunction Assessment Risk Analysis (CARA) program has been performing routine on-orbit satellite conjunction risk analysis for unmanned NASA spacecraft since 2005, and has developed a robust operations procedure and set of recommended best practices for operational conjunction assessment. However, a number of recent developments in Space Situational Awareness and commercial space operations conduct, such as the immanent deployment of much more sensitive space sensing systems and the launching of much larger satellite constellations, have begun to challenge these standard collision risk parameters and calculations. In response CARA has pursued a multi-year evaluation initiative to re-examine risk assessment algorithms and techniques, to develop needed improvements, and to assemble analysis-based operational requirements. This paper gives an overview of the principal parts of the Conjunction Assessment (CA) risk assessment process used at CARA, outlines the technical challenges that each part presents, surveys the possible solutions, and then indicates which particular solution is being recommended for NASA.

Newman, L. K.↗
NASA NTRSDate not supplied

Automated Metadata Scoring Approaches for Earth Observation Data

The Common Metadata Repository (CMR) contains metadata records describing NASA’s Earth observation data products which are archived across 12 data centers also known as Distributed Active Archive Centers (DAACs). To ensure that NASA’s data is discoverable, accessible, and usable, the Analysis and Review of CMR (ARC) Team, located at Marshall Space Flight Center, assesses the quality of these metadata records. The ARC team currently uses a combination of automated and manual methods to check metadata records for quality dimensions such as completeness, correctness, and consistency. In addition to these quality assessments, the team is currently exploring various metadata scoring methods in order to provide normalized results across the twelve DAACs. This method is conducted by using automated methods to assess metadata fields and then provide a numeric score, or grade, based on the analysis. To implement this process, two different approaches have been theorized and are currently being explored by the ARC team. This presentation will describe ARC's two proposed methodologies in more detail, and the pros and cons to using these metadata scoring methods.

Jenny Wood↗
DOE OSTI2020

Extracting dependencies between network assets using deep learning

A network analysis tool receives network flow information and uses deep learning—machine learning that models high-level abstractions in the network flow information—to identify dependencies between network assets. Based on the identified dependencies, the network analysis tool can discover functional relationships between network assets. For example, a network analysis tool receives network flow information, identifies dependencies between multiple network assets based on evaluation of the network flow information, and outputs results of the identification of the dependencies. When evaluating the network flow information, the network analysis tool can pre-process the network flow information to produce input vectors, use deep learning to extract patterns in the input vectors, and then determine dependencies based on the extracted patterns. The network analysis tool can repeat this process so as to update an assessment of the dependencies between network assets on a near real-time basis.

Carroll, Thomas E.↗
DOE OSTI2025

Assessing the climate impact of an improved volcanic sulfate aerosol representation in E3SM

Accurately simulating historical surface temperature variations is essential for evaluating climate models, yet many struggle to reproduce the mid-20th-century temperature trends associated with significant volcanic eruptions. This study examines the impact of volcanic sulfate aerosol representation on these biases using the Energy Exascale Earth System Model (E3SM). The standard CMIP6 protocol prescribes volcanic forcing through radiative perturbations, omitting volcanic aerosol–cloud interactions (VACIs). Here, we implement an emission-based approach with an updated volcanic eruption inventory that directly incorporates volcanic sulfur dioxide (SO 2 ) emissions, enabling a more process-based representation of volcanic forcing. This approach leads to improved surface temperature variability and a modest reduction in cold biases between 1940 and 1980 compared to the CMIP6 setup. Additionally, we assess cloud property responses to a more realistic volcanic sulfate aerosol representation, which weakens cloud-induced cooling during periods of lower volcanic activity. However, despite these refinements, a significant temperature cold bias remains, indicating that further improvements in atmospheric chemistry, aerosol microphysics, cloud processes, and model parameterizations are needed to fully resolve this issue in E3SM.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Measurement System Analysis of a Novel Phase-Based Ultrasonic NDE Technique for Bond Strength Measurement

Fiber reinforced polymer parts have shown tremendous benefits in aerospace structural applications, but their qualification and certification for use in safety critical areas are currently hindered by the lack of a capable non-destructive evaluation (NDE) method or technique for the inspection of these adhesively bonded parts. Conventional NDE methods and techniques typically detect gross bond defects in a qualitative (Pass/Fail) manner. These techniques struggle to detect weak or kissing bonds. Also, there are no widely adopted NDE methods or techniques for measuring interfacial bond strength or detecting kissing bonds. Bond strength is currently ensured by process control and semi-destructive testing. Results from recent research from other authors, including but not limited to mechanical testing, have shown an excellent correlation between interfacial stiffness of an adhesively bonded joint and the adhesive bond strength of that joint. In this paper, a measurement system analysis (MSA) of a novel phase-based ultrasonic NDE Technique, developed at NASA Langley Research Center, is presented for bond strength measurement to assess at an increased level the measurement process and identify components of variation in that measurement process.

Ultrasound↗
DOE OSTI2022

Current challenges in hydrate‐based desalination: Kinetic and thermodynamic perspective

Abstract Water scarcity is becoming a severe problem worldwide due to inadequate freshwater resources and swift population growth. Seawater desalination is one of the vital approaches to meet the demand for freshwater. However, energy and associated costs with conventional seawater desalination techniques are incentivizing non‐conventional water desalination processes. Water desalination using gas hydrates formation is one of the emerging non‐conventional processes. In this perspective article, recent advances in hydrate‐based seawater desalination (HBSD) have been critically analyzed to outline a future path towards a clean and efficient hydrate‐based desalination process. It provides a detailed comparison of various processes developed over decades, and measured desalination efficiencies with their process details. Moreover, the current challenges, limitations, and future perspectives of hydrate‐based desalination are also discussed. The study also recapitulates the thermodynamics and kinetics aspects of the hydrate‐based desalination process. In addition, various factors controlling the desalination efficiencies, such as control of the separation of hydrate crystals, salt deposition on hydrate particles, and hydrate morphology, were thoroughly investigated with their proposed process designs. The kinetics of hydrate formation is also assessed, with the possibility of a zero‐induction regime and its consequent impact on hydrate morphology. The current capabilities of the thermodynamics models (Gibbs energy minimization + electrolyte equation of state) were discussed using various commercially available software. Additionally, the role of hydrate promotors is also discussed, which can reduce the higher cost associated with the hydrate‐based desalination process.

Khan, Muhammad Naveed↗
DOE OSTI2022

On the similarity of hillslope hydrologic function: a clustering approach based on groundwater changes

Abstract. Hillslope similarity is an active topic in hydrology because of its importance in improving our understanding of hydrologic processes and enabling comparisons and paired studies. In this study, we propose a holistic bottom-up hillslope clustering based on a region's integrative hydrodynamic response quantified by the seasonal changes in groundwater levels ΔP. The main advantage of the ΔP clustering is its ability to capture recharge and discharge processes. We test the performance of the ΔP clustering by comparing it to seven other common hillslope clustering approaches. These include clustering approaches based on the aridity index, topographic wetness index, elevation, land cover, and machine-learning that jointly integrate multiple data. We assess the ability of these clustering approaches to identify and categorize hillslopes with similar static characteristics, hydroclimate, land surface processes, and subsurface dynamics in a mountainous watershed – the East River – located in the headwaters of the Upper Colorado River Basin. The ΔP clustering performs very well in identifying hillslopes with six out of the nine characteristics studied. The variability among clusters as quantified by the coefficient of variation (0.2) is less in the ΔP and the machine learning approaches than in the others (> 0.3 for TWI, elevation, and land cover). We further demonstrate the robustness of the ΔP clustering by testing its ability to predict hillslope responses to wet and dry hydrologic conditions, of which it performs well when based on average conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

WaterTAP 0.3 Release

The Water treatment Technoeconomic Assessment Platform (WaterTAP) is an open-source Python-based software package that supports the simulation and optimization of process-scale water treatment trains. WaterTAP seeks to provide the broader water research community with an integrated modeling capability to evaluate cost, energy, and environmental tradeoffs across water treatment options and identify high impact opportunities for innovation including novel materials, processes, and systems. An updated version of WaterTAP is released quarterly and each includes documentation and release notes.

IDAES↗