Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “research methods”

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 1,549 records · Page 86
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Assessment of Heavy-Duty Fueling Methods and Components

Building on the successful commissioning and demonstration of NREL's heavy-duty (HD) fast flow research facility under the Innovating Hydrogen Station's Project, researchers advanced R&D activities to the next phase under a new project titled, Assessment of Heavy-Duty Fueling Methods and Components. This Cooperative Research and Development Agreement (CRADA) is led by NREL in partnership with NextEnergy, Argonne National Laboratory, and Chevron with NextEnergy representing a larger group of industry partners that includes AirLiquide, Hyundai, Nel, Nikola, Shell, and Toyota. The CRADA seeks to develop a comprehensive assessment of HD fuel cell electric vehicle fueling protocols and fueling hardware to understand the effects of fueling protocol architectures on station design, vehicle design, functional safety requirements, and the implications on the total cost of ownership (TCO) and techno economic assessment (TEA).

class 8 truck↗
NASA NTRS2019

Impact of the International Space Station Research Results

The International Space Station (ISS) facilitates research that benefits human lives on Earth and serves as the primary testing ground for technology development to sustain life in the extreme environment of space. To date, investigators have published a wide range of ISS science results, from improved theories about the creation of stars to the outcome of data mining “omics” repositories of previously completed ISS investigations. Because of the unique microgravity environment of the ISS laboratory and the multidisciplinary and international nature of the research, analyzing ISS scientific impacts is an exceptional challenge. As a result, the ISS Program Science Forum (PSF), made up of senior science representatives across the ISS international partnership, uses various methods to describe the impacts of ISS research activities. For the most part, past papers written by PSF members to assess the overall ISS research impact have focused on exhibiting ISS research impact by quantifying ISS research output or its perceived benefits for humanity. This paper proposes a new assessment of ISS impact from the perspective of the end users’ needs. To that end, the authors use visualizations and metrics of scientific publication data to show the ISS research influence on traditional scientific fields, its global reach and the benefits to people across the globe.

Diallo, Ousmane N.↗
NASA NTRS2015

2nd-Order CESE Results For C1.1: Transonic Ringleb Flow

The Conservation Element and Solution Element (CESE) method was used as implemented in the NASA research code ez4d (an unstructured Navier-Stokes solver coded in C++ with serial and parallel versions available.) The CESE method is a time-accurate formulation with flux-conservation in both space and time. The method treats the discretized derivatives of space and time identically and while the 2nd-order accurate version was used, high-order versions exist.

Numerical Analysis↗
NASA NTRS2017

Crew State Monitoring and Line-Oriented Flight Training for Attention Management

Loss of control - inflight (LOC-I) has historically represented the largest category of commercial aviation fatal accidents. A review of worldwide transport airplane accidents (2001-2010) indicated that loss of airplane state awareness (ASA) was responsible for the majority of the LOC-I fatality rate. The Commercial Aviation Safety Team (CAST) ASA study identified 12 major themes that were indicated across the ASA accident and incident events. One of the themes was crew distraction or ineffective attention management, which was found to be involved in all 18 events including flight crew channelized attention, startle/surprise, diverted attention, and/or confirmation bias. Safety Enhancement (SE)-211, "Training for Attention Management" was formed to conduct research to develop and assess commercial airline training methods and realistic scenarios that can address these attention-related human performance limitations. This paper describes NASA SE-211 research for new design approaches and validation of line-oriented flight training (LOFT). Recent accident and incident data suggests that Spatial Disorientation (SD) and Loss-of-Energy State Awareness (LESA) for transport category aircraft are becoming an increasingly prevalent safety concern in all domestic and international operations (Commercial Aviation Safety Team, 2014a). SD is defined as an erroneous perception of aircraft attitude that can lead directly to a Loss-of-Control Inflight (LOC-I) event and result in an accident or incident. LESA is typically characterized by a failure to monitor or understand energy state indications (e.g., airspeed, altitude, vertical speed, commanded thrust) and a resultant failure to maintain safe flight.

Stephens, Chad↗
NASA NTRSDate not supplied

Introduction to the NATO AVT-298 Task Group and Development of the SWiFT Configuration

Reynolds number effects are a key development risk for blended wing body aircraft, particularly at high lift take-off and landing conditions. The full scale aerodynamics of these configurations are thought not to be well represented in industry standard low Reynolds number test facilities and the capability to predict Reynolds number effects using computational fluid dynamics or otherwise is not proven. The NATO AVT-298 research task group was established to investigate these issues and this paper sets out the background, motivations and the collaborative approach as well as the development of a new research configuration to serve as a focus for the research. The ‘SWiFT’ configuration, was developed to exhibit flow physics of interest to the AVT-298 research task group and to be suitable for an experimental campaign. The group collaboratively developed the research configuration to be relevant for related blended-wing-body aircraft programmes using computational fluid dynamics and wing design methods and considering the practicalities of testing. This research targets an improvement in our capability to design, optimise and mature future blended wing body aircraft.

SWiFT↗
NASA NTRS2010

Evaluation of Scaling Methods for Rotorcraft Icing

This paper reports result of an experimental study in the NASA Glenn Icing Research Tunnel (IRT) to evaluate how well the current recommended scaling methods developed for fixed-wing unprotected surface icing applications might apply to representative rotor blades at finite angle of attack. Unlike the fixed-wing case, there is no single scaling method that has been systematically developed and evaluated for rotorcraft icing applications. In the present study, scaling was based on the modified Ruff method with scale velocity determined by maintaining constant Weber number. Models were unswept NACA 0012 wing sections. The reference model had a chord of 91.4 cm and scale model had a chord of 35.6 cm. Reference tests were conducted with velocities of 76 and 100 kt (39 and 52 m/s), droplet MVDs of 150 and 195 fun, and with stagnation-point freezing fractions of 0.3 and 0.5 at angle of attack of 0deg and 5deg. It was shown that good ice shape scaling was achieved for NACA 0012 airfoils with angle of attack lip to 5deg.

Tsao, Jen-Ching↗
NASA NTRS2007

Ultrahigh-Temperature Ceramics

Ultrahigh temperature ceramics (UHTCs) are a class of materials that include the diborides of metals such as hafnium and zirconium. The materials are of interest to NASA for their potential utility as sharp leading edges for hypersonic vehicles. Such an application requires that the materials be capable of operating at temperatures, often in excess of 2,000 C. UHTCs are highly refractory and have high thermal conductivity, an advantage for this application. UHTCs are potentially applicable for other high-temperature processing applications, such as crucibles for molten-metal processing and high-temperature electrodes. UHTCs were first studied in the 1960 s by the U.S. Air Force. NASA s Ames Research Center concentrated on developing materials in the HfB2/SiC family for a leading-edge application. The work focused on developing a process to make uniform monolithic (2-phase) materials, and on the testing and design of these materials. Figure 1 shows arc-jet models made from UHTC materials fabricated at Ames. Figure 2 shows a cone being tested in the arc-jet. Other variations of these materials being investigated elsewhere include zirconium based materials and fiber-reinforced composites. Current UHTC work at Ames covers four broad topics: monoliths, coatings, composites, and processing. The goals include improving the fracture toughness, thermal conductivity and oxidation resistance of monolithic UHTCs and developing oxidation-resistant UHTC coatings for thermal-protection-system substrates through novel coating methods. As part of this effort, researchers are exploring compositions and processing changes that have yielded improvements in properties. Computational materials science and nanotechnology are being explored as approaches to reduce materials development time and improve and tailor properties.

Johnson, Sylvia M.↗
DOE OSTI2026

buhito

buhito is a Python library for graph analysis and machine learning. Graphs can represent networks with objects as nodes and their relationships as edges. buhito focuses on graphlet methods that study graphs through enumerating their component subgraphs to enable interpretable and fast models of complex systems. The package provides tools for different algorithmic designs for computing, analyzing, and applying graphlets to research problems such as machine learning, data compression, and anomaly detection in graph-structured data. A central feature is performing decomposition data analysis on graphs for machine learning models. Implemented in Python and built upon open-source scientific libraries such as NetworkX, NumPy, and SciPy, buhito provides high-performance methods for researchers exploring the mathematical and computational foundations of graphlet analysis applicable to systems of different sizes.

Pimonova, Yulia↗
NASA NTRS1993

A knowledge engineering taxonomy for intelligent tutoring system development

This paper describes a study addressing the issue of developing an appropriate mapping of knowledge acquisition methods to problem types for intelligent tutoring system development. Recent research has recognized that knowledge acquisition methodologies are not general across problem domains; the effectiveness of a method for obtaining knowledge depends on the characteristics of the domain and problem solving task. Southwest Research Institute developed a taxonomy of problem types by evaluating the characteristics that discriminate between problems and grouping problems that share critical characteristics. Along with the problem taxonomy, heuristics that guide the knowledge acquisition process based on the characteristics of the class are provided.

Fink, Pamela K.↗
DOE OSTI2022

Objective Phenotyping of Root System Architecture Using Image Augmentation and Machine Learning in Alfalfa (Medicago sativa L.)

Active breeding programs specifically for root system architecture (RSA) phenotypes remain rare; however, breeding for branch and taproot types in the perennial crop alfalfa is ongoing. Phenotyping in this and other crops for active RSA breeding has mostly used visual scoring of specific traits or subjective classification into different root types. While image-based methods have been developed, translation to applied breeding is limited. This research is aimed at developing and comparing image-based RSA phenotyping methods using machine and deep learning algorithms for objective classification of 617 root images from mature alfalfa plants collected from the field to support the ongoing breeding efforts. Our results show that unsupervised machine learning tends to incorrectly classify roots into a normal distribution with most lines predicted as the intermediate root type. Encouragingly, random forest and TensorFlow-based neural networks can classify the root types into branch-type, taproot-type, and an intermediate taproot-branch type with 86% accuracy. With image augmentation, the prediction accuracy was improved to 97%. Coupling the predicted root type with its prediction probability will give breeders a confidence level for better decisions to advance the best and exclude the worst lines from their breeding program. This machine and deep learning approach enables accurate classification of the RSA phenotypes for genomic breeding of climate-resilient alfalfa.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1979

NASA gear research and its probable effect on rotorcraft transmission design

The NASA Lewis Research Center devised a comprehensive gear technology research program beginning in 1969, the results of which are being integrated into the NASA civilian Helicopter Transmission System Technology Program. Attention is given to the results of this gear research and those programs which are presently being undertaken. In addition, research programs studying pitting fatigue, gear steels and processing, life prediction methods, gear design and dynamics, elastohydrodynamic lubrication, lubrication methods and gear noise are presented. Finally, the impact of advanced gear research technology on rotorcraft transmission design is discussed.

Zaretsky, E. V.↗
NASA NTRS2001

Rhenium Redefined

Through a Small Business Innovation Research (SBIR) contract with NASA's Glenn Research Center, Rhenium Alloys, Inc., of Elyria, Ohio, developed a new method for producing rhenium combustion chambers. Using room temperature isostatic pressing, Rhenium Alloys, Inc., compacted rhenium powder to a high density and into the approximated end shape and dimension of the rocket thruster. The item was then subjected to sintering and containerless hot isostatic pressing, increasing the density of the powder metallurgy part. With the new manufacturing process, both production time and costs are reduced while quality is significantly increased. The method enabled the company to deliver two chemical rocket thrusters to Glenn Research Center. The company makes rhenium a practical choice in manufacturing fields, including the aerospace, nuclear, and electronic industries, with upcoming opportunities projected in medical instrumentation.

Source record↗
DOE OSTI2026

EC-Bench: A Benchmark for Enzyme Commission Number Prediction

Enzymes are proteins that catalyze specific biochemical reactions in cells. Enzyme Commission (EC) numbers are used to annotate enzymes in a four-level hierarchy that classifies enzymes based on the specific chemical reactions they catalyze. Accurate EC number prediction is essential for understanding enzyme functions. Despite the availability of numerous methods for predicting EC numbers from protein sequences, there is no unified framework for evaluating and studying such methods systematically. This gap limits the ability of the community to identify the most effective approaches for enzyme annotation. We introduce EC-Bench, a benchmark for EC number prediction, consisting of 1) an initial representative set of existing methods (including homology-based, deep learning, contrastive learning, and language model methods), 2) existing and novel accuracy and efficiency performance metrics, and 3) selected datasets to allow for comprehensive comparative study. EC-Bench is open-source and provides a framework for researchers to not only compare among existing methods objectively under uniform conditions, but also to introduce and effectively evaluate performance of new methods in a comparative framework. To demonstrate the utility of EC-Bench, we perform extensive experimentation to compare the existing EC number prediction methods and establish their advantages and disadvantages in a variety of prediction tasks, namely “exact EC number prediction”, “EC number completion” and (partial or additional) “EC number recommendation”. We find wide variation in the performance of different methods, but also subtle but potentially useful differences in the performance of different methods across tasks and for different parts of the EC hierarchy.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1995

Link Winds: A visual data analysis system and its application to the atmospheric ozone depletion problem

The Linked Windows Interactive Data System (LinkWinds) is a prototype visual data exploration system resulting from a NASA Jet Propulsion Laboratory (JPL) program of research into the application of graphical methods for rapidly accessing, displaying, and analyzing large multi variate multidisciplinary data sets. Running under UNIX it is an integrated multi-application executing environment using a data-linking paradigm to dynamically interconnect and control multiple windows containing a variety of displays and manipulators. This paradigm, resulting in a system similar to a graphical spreadsheet, is not only a powerful method for organizing large amounts of data for analysis, but leads to a highly intuitive, easy-to-learn user interface. It provides great flexibility in rapidly interacting with large masses of complex data to detect trends, correlations, and anomalies. The system, containing an expanding suite of non-domain-specific applications, provides for the ingestion of a variety of data base formats and hard -copy output of all displays. Remote networked workstations running LinkWinds may be interconnected, providing a multiuser science environment (MUSE) for collaborative data exploration by a distributed science team. The system is being developed in close collaboration with investigators in a variety of science disciplines using both archived and real-time data. It is currently being used to support the Microwave Limb Sounder (MLS) in orbit aboard the Upper Atmosphere Research Satellite (UARS). This paper describes the application of LinkWinds to this data to rapidly detect features, such as the ozone hole configuration, and to analyze correlations between chemical constituents of the atmosphere.

Jacobson, Allan S.↗
DOE OSTI2025

Assessing the potential of deep learning for protein–ligand docking

The effects of ligand binding on protein structures and their in vivo functions carry numerous implications for modern biomedical research and biotechnology development efforts such as drug discovery. Although several deep learning (DL) methods and benchmarks designed for protein–ligand docking have recently been introduced, so far no previous works have systematically studied the behaviour of the latest docking and structure prediction methods within the broadly applicable context of: (1) using predicted (apo) protein structures for docking (for example, for applicability to new proteins); (2) binding multiple (cofactor) ligands concurrently to a given target protein (for example, for enzyme design); and (3) having no previous knowledge of binding pockets (for example, for generalization to unknown pockets). To enable a deeper understanding of the real-world utility of docking methods, we introduce PoseBench, a comprehensive benchmark for broadly applicable protein–ligand docking. PoseBench enables researchers to rigorously and systematically evaluate DL methods for apo-to-holo protein–ligand docking and protein–ligand structure prediction using both primary ligand and multiligand benchmark datasets, the latter of which we introduce to the DL community. Empirically, using PoseBench, we find that: (1) DL cofolding methods generally outperform comparable conventional and DL docking baseline algorithms, but popular methods such as AlphaFold 3 are still challenged by prediction targets with new protein–ligand binding poses; (2) certain DL cofolding methods are highly sensitive to their input multiple sequence alignments, whereas others are not; and (3) DL methods struggle to strike a balance between structural accuracy and chemical specificity when predicting new or multiligand protein targets.

Morehead, Alex [Lawrence Berkeley National Laborat↗
NASA NTRS1994

Numerical simulation of the flow about the F-18 HARV at high angle of attack

As part of NASA's High Alpha Technology Program, research has been aimed at developing and extending numerical methods to accurately predict the high Reynolds number flow about the NASA F-18 High Alpha Research Vehicle (HARV) at large angles of attack. The HARV aircraft is equipped with a bidirectional thrust vectoring unit which enables stable, controlled flight through 70 deg angle of attack. Currently, high-fidelity numerical solutions for the flow about the HARV have been obtained at alpha = 30 deg, and validated against flight-test data. It is planned to simulate the flow about the HARV through alpha = 60 deg, and obtain solutions of the same quality as those at the lower angles of attack. This report presents the status of work aimed at extending the HARV computations to the extreme angle of attack range.

Murman, Scott M.↗
DOE OSTI2022

A Universal Refrigerant Charge Fault Detection and Diagnostics Method Based on Pump Down Operation

The performance of the heat pump system varies greatly depending on the refrigerant charge amount. Improving the refrigerant charge fault detection and diagnostics (FDD) method of vapor compression systems have the potential for increasing energy efficiency and reducing service cost. Previous studies to predict refrigerant charge amount are mostly empirical methods which require significant amount of experimental data for high accuracy. The primary goal of this research is to develop a universal charge fault detection method which requires only a few experimental data with high prediction accuracy.Currently, pump down operations are typical practices by HVAC technicians when they need to open the refrigerant circuit to make a repairment. In addition, compressors have a built-in low-pressure cut-off protection function, and the compressor performance maps are commonly available from manufacturers. The proposed method innovatively utilizes the typical pump down operation, the compressor low-pressure cut-off protection, and the compressor performance map. It does not require any geometry information of heat exchangers, refrigerant lines, or charge buffers.The new charge prediction method is firstly formulated through theoretical analysis, then verified and calibrated by a quasi-steady-state simulation of the pump down process for a residential heat pump system. The quasi steady-state simulation uses an HVAC system simulation framework driven by DOE/ORNL Heat Pump Design Model (HPDM). Preliminary experiment validations with heat pump refrigerant leakage tests demonstrate the deviation of the proposed charge prediction method compared with measurement is within 8%. This technology makes refrigerant charge amount available at the technician’s fingertips and leads to shorter maintenance time and fewer site visits.

Li, Zhenning↗
NASA NTRS2005

Investigation of the Utilization of Modern Industrial Methods, Processes, Ergonomics, and the Internet in the Scientific Environment

On Oct. 1, 2001 Cleveland State University and NASA Glenn Research Center embarked on the above named cooperative agreement. Because NASA's research facilities often exhibit instances where the failure to use state-of-the-art technologies and methods to improve on outmoded systems of interface and control, and this runs contrary to the NASA philosophy of "faster, better, and cheaper", it was deemed an ideal opportunity for this collaboration. The main objectives of the proposed effort were to research and investigate the use of the latest technologies, methods, techniques, etc. which pertain to control and interface with industrial and research systems and facilities. The work was done in large part at NASA Glenn Research Center, using selected research facilities as real-world laboratories; such as certain Microgravity Science Division and Space Station projects. Microgravity Science Division at Glenn Research Center designs and builds experiments to be flown on the Space Shuttle and eventually on the International Space Station. Economy of space, weight, complexity, data storage, ergonomics, and many other factors present problems that also exist in industry. Many of the solutions can come from the same areas of study mentioned above.

Myer, Spencer S., Jr.↗