Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “factorization machine”

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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Depot Charging Schedule Optimization for Medium- and Heavy-Duty Battery-Electric Trucks

Charge management, which lowers charging costs for fleets and prevents straining the electrical grid, is critical to the successful deployment of medium- and heavy-duty battery-electric trucks (MHD BETs). This study introduces an energy demand and cost management framework that optimizes depot charging for MHD BETs by combining an energy consumption machine learning model and a linear program optimization model. The framework considers key factors impacting real-world MHD BET operations, including vehicle and charger configurations, duty cycles, use cases, geographic and climate conditions, operation schedules, and utilities’ time-of-use (TOU) rates and demand charges. The framework was applied to a hypothetical fleet of 100 MHD BETs in California under three different utilities for 365 days, with results compared to unmanaged charging. The optimized charging solution avoided more than 90% of on-peak charging, reduced fleet charging peak load by 64–75%, and lowered fleet energy variable costs by 54–64%. This study concluded that the proposed charge management framework significantly reduces energy costs and peak loads for MHD BET fleets while making recommendations for fleet electrification infrastructure planning and the design of utility TOU rates and demand charges.

Song, Shuhan↗
DOE OSTI2025

ELM2.1-XGBfire1.0: improving wildfire prediction by integrating a machine learning fire model in a land surface model

Wildfires have shown increasing trends in both frequency and severity across the contiguous United States (CONUS). However, process-based fire models have difficulties in accurately simulating the burned area over the CONUS due to a simplification of the physical process and cannot capture the interplay among fire, ignition, climate, and human activities. The deficiency of burned area simulation deteriorates the description of fire impact on energy balance, water budget, and carbon fluxes in the Earth system models (ESMs). Alternatively, fire models based on machine learning (ML), which capture statistical relationships between the burned area and environmental factors, have shown promising burned area predictions and corresponding fire impact simulation. We develop a hybrid framework (ELM2.1-XGBFire1.0) that integrates an eXtreme Gradient Boosting (XGBoost) wildfire model with the Energy Exascale Earth System Model (E3SM) land model (ELM) version 2.1. A Fortran–C–Python deep learning bridge is adapted to support online communication between ELM and the ML fire model. Specifically, the burned area predicted by the ML-based wildfire model is directly passed to ELM to adjust the carbon pool and vegetation dynamics after disturbance, which are then used as predictors in the ML-based fire model in the next time step. Evaluated against the historical burned area from Global Fire Emissions Database 5 from 2001–2019, the ELM2.1-XGBFire1.0 outperforms process-based fire models in terms of spatial distribution and seasonal variations. The ELM2.1-XGBFire1.0 has proven to be a new tool for studying vegetation–fire interactions and, more importantly, enables seamless exploration of climate–fire feedback, working as an active component of E3SM.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1977

Factors affecting laser-trim stability of thick film resistors

Various factors affecting precision of trim and resistor stability were considered. The influence of machine operating parameters on resistor performance was examined and quantified through statistically designed experiments for a Q switched YAG laser system. Laser kerf quality was studied by scanning electron microscopy and related to kerf isolation resistance measurements. A relatively simple production oriented, quality control test is proposed for rapid determination of kerf electrical stability. In addition, the effect of cut design and extent of trim on precision and stability were discussed.

Cote, R. E.↗
NASA NTRS2000

Design and Evaluation of a New Boundary-Layer Rake for Flight Testing

A new boundary-layer rake has been designed and built for flight testing on the NASA Dryden Flight Research Center F-15B/Flight Test Fixture. A feature unique to this rake is its curved body, which allows pitot tubes to be more densely clustered in the near-wall region than conventional rakes allow. This curved rake design has a complex three-dimensional shape that requires innovative solid-modeling and machining techniques. Finite-element stress analysis of the new design shows high factors of safety. The rake has passed a ground test in which random vibration measuring 12 g rms was applied for 20 min in each of the three normal directions. Aerodynamic evaluation of the rake has been conducted in the NASA Glenn Research Center 8 x 6 Supersonic Wind Tunnel at Mach 0-2. The pitot pressures from the new rake agree with conventional rake data over the range of Mach numbers tested. The boundary-layer profiles computed from the rake data have been shown to have the standard logarithmic-law profile. Skin friction values computed from the rake data using the Clauser plot method agree with the Preston tube results and the van Driest II compressible skin friction correlation to approximately +/-5 percent.

Bui, Trong T.↗
NASA NTRS2007

Seeking to Improve Low Energy Neutral Atom Detection in Space

The detection of energetic neutral atoms allows for the remote examination of the interactions between plasmas and neutral populations in space. Before these neutral atoms can be measured, they must first be converted to ions. For the low energy end of this spectrum, interaction with a conversion surface is often the most efficient method to convert neutrals into ions. It is generally thought that the most efficient surfaces are low work functions materials. However, by their very nature, these surfaces are highly reactive and unstable, and therefore are not suitable for space missions where conditions cannot be controlled as they are in a laboratory. We therefore are looking to optimize a stable surface for conversion efficiency. Conversion efficiency can be increased either by changing the incident angle of the neutral particles to be grazing incidence and using stable surfaces with high conversion efficiencies. We have examined how to increase the angle of incidence from -80 degrees to -89 degrees, while maintaining or improving the total active conversion surface area without increasing the overall volume of the instrument. We are developing a method to micro-machine silicon, which will reduce the volume to surface area ratio by a factor of 60. We have also examined the material properties that affect the conversion efficiency of the surface for stable surfaces. Some of the parameters we have examined are work function, smoothness, and bond structure. We find that for stable surfaces, the most important property is the smoothness of the surface.

Shappirio, M.↗
DOE OSTI2025

Trustworthiness and Trust: Identifying Factors that Drive Successful Human-AI Interaction in Nuclear Power Plant Applications

Emerging technologies such as artificial intelligence (AI) and machine learning (ML) are rapidly evolving and considered a promising tool for efficient and continued safe operations of the U.S. nuclear power plants (NPPs). Emerging AI techniques like large language models (LLMs) are one such technology that may support personnel at existing NPPs perform work more efficiently. For example, operators may query the current operational status of a power plant via a chat interface leveraging LLMs to access plant-related information in an interactive manner rather than manually collecting various sensor data for tasks such as surveillances or completing work orders. This is a fundamental shift in the way operators currently perform their tasks today. The literature of human-automation interaction indicates that trust is a crucial factor that drives successful interaction between a human operator and an automated system, like an AI-infused NPP application. This work presents the results of a literature review on key factors that relate to trust in AI/LLM technologies for NPP applications. The relevant literature of human factors and cognitive engineering has identified various factors related to trust including trustworthiness, performance characteristics, operator skill and perceived risk. This preliminary literature review will guide development and evaluation of models involving the identified factors influencing trust in AI and develop a framework for human-centered design for interface between humans and AI. By addressing trust, this work supports developing a technical basis for designing key characteristics of AI/LLM to support calibrated trust, which will ultimately support wide-scale adoption of AI/LLM technologies, as well as ensure safe, effective, and reliable use.

99 - GENERAL AND MISCELLANEOUS↗
NASA NTRS1994

On the use of the systems approach to certify advanced aviation technologies

The field of human factors is as varied and diverse as the human subject itself. But one of its most important applications is the facilitation of safety and efficiency in a particular working environment through the implementation of paradigms known about humans and their working relationship with machines and systems. During the period since World War II (which is often viewed as the birth of Human Factors) no area has been the subject of more human factors research than aviation. And in no time during that epoch is the influence of human factors more important, nor more imperative than it is today. As technology driven designs have been finding their way into the national airspace system (NAS), there has been growing concern within the aviation industry itself, the Federal Aviation Administration (FAA), and the general public for a means by which to certify complex systems and the advanced aviation technologies that will be responsible for transporting, directing, and maintaining our airborne travel. While it is widely agreed human factors certification is desirable, the philosophy that will underlie the approach is debatable. There are, in general, two different approaches to certification: (1) the top-down or systems approach; and, (2) the bottom-up or monadical approach. The top-down approach is characterized by the underlying assumption that certification can be best achieved by looking at the system as a whole, understanding its objectives and operating environment, then examining the constituent parts. In an aircraft cockpit, this would be accomplished by first examining what the aircraft is supposed to be (e.g., fighter, general aviation, passenger), identifying its operating environment (IFR, VMC, combat, etc.) and looking at the entire working system which includes the hardware, software, liveware and their interactions; then, evaluative measures can be applied to the subsystems (e.g., individual instruments, CRT displays, controls). The bottom-up approach is founded on the philosophy that the whole can be best served by first examining it constituent elements. This approach would perform the above certification completely antithetically, by looking at the individual parts and certifying good human factors applications to those parts under the basic assumption that the whole is equal to the sum of its parts.

Wise, Mark A.↗
NASA NTRS1997

A Human Factors Analysis of EVA Time Requirements

Human Factors Engineering (HFE) is a discipline whose goal is to engineer a safer, more efficient interface between humans and machines. HFE makes use of a wide range of tools and techniques to fulfill this goal. One of these tools is known as motion and time study, a technique used to develop time standards for given tasks. During the summer of 1995, a human factors motion and time study was initiated with the goals of developing a database of EVA task times and developing a method of utilizing the database to predict how long an EVA should take. Initial development relied on the EVA activities performed during the STS-61 (Hubble) mission. The first step of the study was to become familiar with EVA's, the previous task-time studies, and documents produced on EVA's. After reviewing these documents, an initial set of task primitives and task-time modifiers was developed. Data was collected from videotaped footage of two entire STS-61 EVA missions and portions of several others, each with two EVA astronauts. Feedback from the analysis of the data was used to further refine the primitives and modifiers used. The project was continued during the summer of 1996, during which data on human errors was also collected and analyzed. Additional data from the STS-71 mission was also collected. Analysis of variance techniques for categorical data was used to determine which factors may affect the primitive times and how much of an effect they have. Probability distributions for the various task were also generated. Further analysis of the modifiers and interactions is planned.

Pate, Dennis W.↗
DOE OSTI2025

NETL RDE Image Classification Dataset 2020 - 10 Classes

Dataset including high-speed down-axis RDE images used for updated image classification study. This dataset includes 100,000 images with 10 classifications: 1CW, 1CCW, 2CW, 2CCW, 3CW, 3CCW, and Deflagration. Images are cropped to center annulus, and resized to 301x301 pixels. Images are filtered using the AFRL Beta correction factor.

AS↗
NASA NTRS2016

Taxi-Out Time Prediction for Departures at Charlotte Airport Using Machine Learning Techniques

Predicting the taxi-out times of departures accurately is important for improving airport efficiency and takeoff time predictability. In this paper, we attempt to apply machine learning techniques to actual traffic data at Charlotte Douglas International Airport for taxi-out time prediction. To find the key factors affecting aircraft taxi times, surface surveillance data is first analyzed. From this data analysis, several variables, including terminal concourse, spot, runway, departure fix and weight class, are selected for taxi time prediction. Then, various machine learning methods such as linear regression, support vector machines, k-nearest neighbors, random forest, and neural networks model are applied to actual flight data. Different traffic flow and weather conditions at Charlotte airport are also taken into account for more accurate prediction. The taxi-out time prediction results show that linear regression and random forest techniques can provide the most accurate prediction in terms of root-mean-square errors. We also discuss the operational complexity and uncertainties that make it difficult to predict the taxi times accurately.

Safe and efficient surface operations↗
DOE OSTI2024

Identification of carbohydrate gene clusters obtained from in vitro fermentations as predictive biomarkers of prebiotic responses

Prebiotic fibers are non-digestible substrates that modulate the gut microbiome by promoting expansion of microbes having the genetic and physiological potential to utilize those molecules. Although several prebiotic substrates have been consistently shown to provide health benefits in human clinical trials, responder and non-responder phenotypes are often reported. These observations had led to interest in identifying, a priori, prebiotic responders and non-responders as a basis for personalized nutrition. In this study, we conducted in vitro fecal enrichments and applied shotgun metagenomics and machine learning tools to identify microbial gene signatures from adult subjects that could be used to predict prebiotic responders and non-responders. Using short chain fatty acids as a targeted response, we identified genetic features, consisting of carbohydrate active enzymes, transcription factors and sugar transporters, from metagenomic sequencing of in vitro fermentations for three prebiotic substrates: xylooligosacharides, fructooligosacharides, and inulin. A machine learning approach was then used to select substrate-specific gene signatures as predictive features. These features were found to be predictive for XOS responders with respect to SCFA production in an in vivo trial. Our results confirm the bifidogenic effect of commonly used prebiotic substrates along with inter-individual microbial responses towards these substrates. We successfully trained classifiers for the prediction of prebiotic responders towards XOS and inulin with robust accuracy (≥ AUC 0.9) and demonstrated its utility in a human feeding trial. Overall, the findings from this study highlight the practical implementation of pre-intervention targeted profiling of individual microbiomes to stratify responders and non-responders.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1995

The scheme machine: A case study in progress in design derivation at system levels

The Scheme Machine is one of several design projects of the Digital Design Derivation group at Indiana University. It differs from the other projects in its focus on issues of system design and its connection to surrounding research in programming language semantics, compiler construction, and programming methodology underway at Indiana and elsewhere. The genesis of the project dates to the early 1980's, when digital design derivation research branched from the surrounding research effort in programming languages. Both branches have continued to develop in parallel, with this particular project serving as a bridge. However, by 1990 there remained little real interaction between the branches and recently we have undertaken to reintegrate them. On the software side, researchers have refined a mathematically rigorous (but not mechanized) treatment starting with the fully abstract semantic definition of Scheme and resulting in an efficient implementation consisting of a compiler and virtual machine model, the latter typically realized with a general purpose microprocessor. The derivation includes a number of sophisticated factorizations and representations and is also deep example of the underlying engineering methodology. The hardware research has created a mechanized algebra supporting the tedious and massive transformations often seen at lower levels of design. This work has progressed to the point that large scale devices, such as processors, can be derived from first-order finite state machine specifications. This is roughly where the language oriented research stops; thus, together, the two efforts establish a thread from the highest levels of abstract specification to detailed digital implementation. The Scheme Machine project challenges hardware derivation research in several ways, although the individual components of the system are of a similar scale to those we have worked with before. The machine has a custom dual-ported memory to support garbage collection. It consists of four tightly coupled processes--processor, collector, allocator, memory--with a very non-trivial synchronization relationship. Finally, there are deep issues of representation for the run-time objects of a symbolic processing language. The research centers on verification through integrated formal reasoning systems, but is also involved with modeling and prototyping environments. Since the derivation algebra is basd on an executable modeling language, there is opportunity to incorporate design animation in the design process. We are looking for ways to move smoothly and incrementally from executable specifications into hardware realization. For example, we can run the garbage collector specification, a Scheme program, directly against the physical memory prototype, and similarly, the instruction processor model against the heap implementation.

Johnson, Steven D.↗
NASA NTRS1994

Statistical Analysis of NAS Parallel Benchmarks and LINPACK Results

In the last three years extensive performance data have been reported for parallel machines both based on the NAS Parallel Benchmarks, and on LINPACK. In this study we have used the reported benchmark results and performed a number of statistical experiments using factor, cluster, and regression analyses. In addition to the performance results of LINPACK and the eight NAS parallel benchmarks, we have also included peak performance of the machine, and the LINPACK n and n(sub 1/2) values. Some of the results and observations can be summarized as follows: 1) All benchmarks are strongly correlated with peak performance. 2) LINPACK and EP have each a unique signature. 3) The remaining NPB can grouped into three groups as follows: (CG and IS), (LU and SP), and (MG, FT, and BT). Hence three (or four with EP) benchmarks are sufficient to characterize the overall NPB performance. Our poster presentation will follow a standard poster format, and will present the data of our statistical analysis in detail.

Meuer, Hans-Werner↗
NASA NTRS1980

Research in the application of spectral data to crop identification and assessment, volume 2

The development of spectrometry crop development stage models is discussed with emphasis on models for corn and soybeans. One photothermal and four thermal meteorological models are evaluated. Spectral data were investigated as a source of information for crop yield models. Intercepted solar radiation and soil productivity are identified as factors related to yield which can be estimated from spectral data. Several techniques for machine classification of remotely sensed data for crop inventory were evaluated. Early season estimation, training procedures, the relationship of scene characteristics to classification performance, and full frame classification methods were studied. The optimal level for combining area and yield estimates of corn and soybeans is assessed utilizing current technology: digital analysis of LANDSAT MSS data on sample segments to provide area estimates and regression models to provide yield estimates.

Daughtry, C. S. T.↗
NASA NTRS1981

Symposium on Aviation Psychology, 1st, Ohio State University, Columbus, OH, April 21, 22, 1981, Proceedings

The impact of modern technology on the role, responsibility, authority, and performance of human operators in modern aircraft and ATC systems was examined in terms of principles defined by Paul Fitts. Research into human factors in aircraft operations and the use of human factors engineering for aircraft safety improvements were discussed, and features of the man-machine interface in computerized cockpit warning systems are examined. The design and operational features of computerized avionics displays and HUDs are described, along with results of investigations into pilot decision-making behavior, aircrew procedural compliance, and aircrew judgment training programs. Experiments in vision and visual perception are detailed, as are behavioral studies of crew workload, coordination, and complement. The effectiveness of pilot selection, screening, and training techniques are assessed, as are methods for evaluating pilot performance.

Source record↗
NASA NTRS1990

Engineering specification and system design for CAD/CAM of custom shoes: UMC project effort

Further experimentations were made to improve the design and fabrication techniques of the integrated sole. The sole design is shown to be related to the foot position requirements and the actual shape of the foot including presence of neurotropic ulcers or other infections. Factors for consideration were: heel pitch, balance line, and rigidity conditions of the foot. Machining considerations were also part of the design problem. Among these considerations, widths of each contour, tool motion, tool feed rate, depths of cut, and slopes of cut at the boundary were the key elements. The essential fabrication techniques evolved around the idea of machining a mold then, using quick-firm latex material, casting the sole through the mold. Two main mold materials were experimented with: plaster and wood. Plaster was very easy to machine and shape but could barely support the pressure in the hydraulic press required by the casting process. Wood was found to be quite effective in terms of relative cost, strength, and surface smoothness except for the problem of cutting against the fibers which could generate ragged surfaces. The programming efforts to convert the original dBase programs into C programs so that they could be executed on the SUN Computer at North Carolina State University are discussed.

Bao, Han P.↗
NASA NTRS2001

Cell-cycle research with synchronous cultures: an evaluation

The baby-machine system, which produces new-born Escherichia coli cells from cultures immobilized on a membrane, was developed many years ago in an attempt to attain optimal synchrony with minimal disturbance of steady-state growth. In the present article, we put forward a model to describe the behaviour of cells produced by this method, and provide quantitative evaluation of the parameters involved, at each of four different growth rates. Considering the high level of selection achievable with this technique and the natural dispersion in interdivision times, we believe that the output of the baby machine is probably close to optimal in terms of both quality and persistence of synchrony. We show that considerable information on events in the cell cycle can be obtained from populations with age distributions very much broader than those achieved with the baby machine and differing only modestly from steady state. The data presented here, together with the long and fruitful history of findings employing the baby-machine technique, suggest that minimisation of stress on cells is the single most important factor for successful cell-cycle analysis.

Non-NASA Center↗
NASA NTRS1982

Space station automation and autonomy - Advantages and problems

Design guidelines and functional systems being considered in the process of defining the configuration of the automated systems for a manned space station are outlined. The requirements are dependent on life-cycle costing and will set the necessary level of automation, as well as autonomy from outside commands. Fault protection routines have been largely devised according to successful programming on the Voyager spacecraft. An analysis is still needed of the housekeeping functions, including human necessities, machine functions, and mission objectives. A data base will result, defining the functions that have historically been delegated to either man or machine. Care must be taken to coordinate and document stationkeeping functions that might interface with mission functions. A data management system that is flexible with regards to changing mission objectives and to the MTBF factors, which will determine the level of technology to be used is required. Expert systems will be integrated into the automation to guide the machines in problem solving, including ensuring adequate management of the battery subsystem.

Carlisle, R. F.↗