SEARCH · Engineering Papers

Results for “reliability metrics”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 559 records · Page 31

All sources NASA NTRS DOE OSTI

DOE OSTI2022

How Reproducible are Surface Areas Calculated from the BET Equation?

Abstract Porosity and surface area analysis play a prominent role in modern materials science. At the heart of this sits the Brunauer–Emmett–Teller (BET) theory, which has been a remarkably successful contribution to the field of materials science. The BET method was developed in the 1930s for open surfaces but is now the most widely used metric for the estimation of surface areas of micro‐ and mesoporous materials. Despite its widespread use, the calculation of BET surface areas causes a spread in reported areas, resulting in reproducibility problems in both academia and industry. To prove this, for this analysis, 18 already‐measured raw adsorption isotherms were provided to sixty‐one labs, who were asked to calculate the corresponding BET areas. This round‐robin exercise resulted in a wide range of values. Here, the reproducibility of BET area determination from identical isotherms is demonstrated to be a largely ignored issue, raising critical concerns over the reliability of reported BET areas. To solve this major issue, a new computational approach to accurately and systematically determine the BET area of nanoporous materials is developed. The software, called “BET surface identification” (BETSI), expands on the well‐known Rouquerol criteria and makes an unambiguous BET area assignment possible.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Meeting Global Health Needs via Infectious Disease Forecasting: Development of a Reliable Data-Driven Framework

Infectious diseases (IDs) have a significant detrimental impact on global health. Timely and accurate ID forecasting can result in more informed implementation of control measures and prevention policies. To meet the operational decision-making needs of real-world circumstances, we aimed to build a standardized, reliable, and trustworthy ID forecasting pipeline and visualization dashboard that is generalizable across a wide range of modeling techniques, IDs, and global locations. We forecasted 6 diverse, zoonotic diseases (brucellosis, campylobacteriosis, Middle East respiratory syndrome, Q fever, tick-borne encephalitis, and tularemia) across 4 continents and 8 countries. We included a wide range of statistical, machine learning, and deep learning models (n=9) and trained them on a multitude of features (average n=2326) within the One Health landscape, including demography, landscape, climate, and socioeconomic factors. The pipeline and dashboard were created in consideration of crucial operational metrics—prediction accuracy, computational efficiency, spatiotemporal generalizability, uncertainty quantification, and interpretability—which are essential to strategic data-driven decisions. While no single best model was suitable for all disease, region, and country combinations, our ensemble technique selects the best-performing model for each given scenario to achieve the closest prediction. For new or emerging diseases in a region, the ensemble model can predict how the disease may behave in the new region using a pretrained model from a similar region with a history of that disease. The data visualization dashboard provides a clean interface of important analytical metrics, such as ID temporal patterns, forecasts, prediction uncertainties, and model feature importance across all geographic locations and disease combinations. As the need for real-time, operational ID forecasting capabilities increases, this standardized and automated platform for data collection, analysis, and reporting is a major step forward in enabling evidence-based public health decisions and policies for the prevention and mitigation of future ID outbreaks.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2026

Integrated Computational Materials Engineering (ICME) Capability Maturity Levels for Ecosystems Enabling Digital Transformation

Digital engineering (DE) and integrated computational materials engineering (ICME) are widely recognized as critical enablers of faster, more affordable, and more reliable aerospace systems. However, many organizations have struggled to realize the promised return on investment (ROI) from digital initiatives. A primary reason is the absence of a shared, decision-focused framework that distinguishes simple digitization of existing workflows from true digital transformation that fundamentally changes how engineering decisions are made. This paper introduces an ICME capability maturity framework that fills this gap. The framework defines six cumulative ICME capability maturity levels (CMLs), explicitly tied to decision authority, engineering integration, optimization, and uncertainty management across material, process, structure, and performance scales. It is designed to complement established readiness metrics such as technology readiness levels (TRLs), manufacturing readiness levels (MRLs), and integration readiness levels (IRLs), by addressing a missing dimension: the conditions required for model-informed decision authority across scales. A unifying figure and capability table illustrate the six-level ICME Capability Maturity Framework, showing how organizations progress from digitization—with limited or negative ROI—to true digital transformation, where ICME-enabled workflows deliver measurable improvements in decision quality, cycle time, risk reduction, and reuse. The framework is intended for both technical practitioners and executive leadership, providing a common language to assess current state, guide roadmaps, align software ecosystem investments, and set realistic expectations for digital transformation outcomes. A regulatory-relevant statement clarifying the relationship between ICME capability and existing certification frameworks is provided.

ICME↗

NASA NTRS2019

Application of Machine Learning Techniques to Delay Tolerant Network Routing

This dissertation discusses several machine learning techniques to improve routing in delay tolerant networks (DTNs). These are networks in which there may be long one-way trip times, asymmetric links, high error rates, and deterministic as well as non-deterministic loss of contact between network nodes, such as interplanetary satellite networks, mobile ad hoc networks and wireless sensor networks. This work uses historical network statistics to train a multi-label classifier to predict reliable paths through the network. In addition, a clustering technique is used to predict future mobile node locations. Both of these techniques are used to reduce the consumption of resources such as network bandwidth, memory and data storage that is required by replication routing methods often used in opportunistic DTN environments. Thesis contributions include: an emulation tool chain developed to create a DTN test bed for machine learning, the network and software architecture for a machine learning based routing method, the development and implementation of classification and clustering techniques and performance evaluation in terms of machine learning and routing metrics.

Dudukovich, Rachel M.↗

NASA NTRS1994

Implementing Software Safety in the NASA Environment

Until recently, NASA did not consider allowing computers total control of flight systems. Human operators, via hardware, have constituted the ultimate safety control. In an attempt to reduce costs, NASA has come to rely more and more heavily on computers and software to control space missions. (For example. software is now planned to control most of the operational functions of the International Space Station.) Thus the need for systematic software safety programs has become crucial for mission success. Concurrent engineering principles dictate that safety should be designed into software up front, not tested into the software after the fact. 'Cost of Quality' studies have statistics and metrics to prove the value of building quality and safety into the development cycle. Unfortunately, most software engineers are not familiar with designing for safety, and most safety engineers are not software experts. Software written to specifications which have not been safety analyzed is a major source of computer related accidents. Safer software is achieved step by step throughout the system and software life cycle. It is a process that includes requirements definition, hazard analyses, formal software inspections, safety analyses, testing, and maintenance. The greatest emphasis is placed on clearly and completely defining system and software requirements, including safety and reliability requirements. Unfortunately, development and review of requirements are the weakest link in the process. While some of the more academic methods, e.g. mathematical models, may help bring about safer software, this paper proposes the use of currently approved software methodologies, and sound software and assurance practices to show how, to a large degree, safety can be designed into software from the start. NASA's approach today is to first conduct a preliminary system hazard analysis (PHA) during the concept and planning phase of a project. This determines the overall hazard potential of the system to be built. Shortly thereafter, as the system requirements are being defined, the second iteration of hazard analyses takes place, the systems hazard analysis (SHA). During the systems requirements phase, decisions are made as to what functions of the system will be the responsibility of software. This is the most critical time to affect the safety of the software. From this point, software safety analyses as well as software engineering practices are the main focus for assuring safe software. While many of the steps proposed in this paper seem like just sound engineering practices, they are the best technical and most cost effective means to assure safe software within a safe system.

Wetherholt, Martha S.↗

DOE OSTI2024

Assessing the Sensitivity of Pourbaix Diagrams to Computational Protocols: Electrochemical Stability of Ni Oxides as a Case Study

Pourbaix diagrams stand as a useful tool in assessing and visualizing materials’ electrochemical stability and are widely used for electrocatalyst design. However, their reliability hinges on the accuracy of the chemical potentials of involved phases, which may bear uncertainties and can be significantly impacted by decision-making steps in the computational protocol. Here, this study introduces a robust sensitivity analysis framework, exemplified through a detailed examination of the computational Pourbaix diagram of Ni, the oxides of which are used as high-activity and cost-friendly catalysts for many electrochemical reactions. Quantities of interest derived from the Pourbaix diagram include the appearance and stability domain of the catalytically active Ni oxide phases along with the onset electrochemical potentials of phase transitions. These metrics can guide the design of operational conditions for Ni oxide electrocatalysts. We find that the employed DFT exchange-correlation functional has the most significant influence on the computed Pourbaix diagram. Uncertainties on crystal structures, along with their related ab initio energetics, are also found to affect the size of the phase stability domain. Higher-order coupling among input parameters is found to play a crucial role in influencing the appearance and distribution of Ni phases in the diagram. Our findings suggest a need to consider variations and uncertainties associated with the computational procedures on predicted Pourbaix diagrams for materials design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1984

Communications-imposed pilot workload - A comparison of sixteen estimation techniques

Sixteen potential metrics of mental workload were investigated in regard to their relative sensitivity to communications load and their differential intrusion on primary task performance. A moving-base flight simulator was used to present three cross-country flights to each of 30 subject pilots, each flight varying only in the difficulty of the inherent communications requirements. With the exception of the rating scale measures, which were obtained immediately post-flight, all measures were taken over a seven minute segment of the flight task. The results indicated that both the Modified Cooper-Harper and the workload Multi-descriptor rating scales were reliably sensitive to changes in communications load. Also, the secondary task measure of time estimation and the physiological measure of pupil diameter yielded sensitivity. As expected, those primary task measures which were direct measures of communicative performance were also sensitive to load, while aircraft control primary task measures were not, attesting to the task-specificity of such measures. Finally, the intrusion analysis revealed no differential interference between workload measures.

Casali, J. G.↗

DOE OSTI2021

A Comprehensive Framework for Valuation of Ecosystem Services in the Context of Hydropower

While models to value ecosystem services exist, they suffer from a lack of “portability” in the sense that a single modelling framework developed for one site cannot be imported and applied to another. Additionally, benefit estimations are often fragmented, incomplete, incomparable, and in heterogenous metrics, thus preventing aggregation to arrive at one comprehensive value. In the context of hydropower, the methods, as well as the metrics used to value the associated ecosystem services, vary between stakeholders (e.g., competing water users, agencies, etc.), detracting from the ability to assess the total value of a hydropower project, water management schemes, or comparing value between competing water users. Further, current methods to value water neglect non-market ecosystem services’ values by failing to account for externalities, resulting in misallocation of costs (e.g., obligatory stakeholder payments for water use) and misinterpretation of hydropower benefits. The benefit-cost ratios in hydropower development are often incomplete because non-market benefits are excluded (e.g., benefits, such as fish habitat resiliency and agricultural water reliability, derived from hydropower development). An approach to enable consistent, standardized hydropower benefit-cost analyses does not currently exist. This paper conceptualizes a methodology to standardize ecosystem services valuation in the context of hydropower projects through the integration of the U.S. Environmental Protection Agency’s existing Final Ecosystem Goods and Services Classification System framework and economic valuation techniques, and demonstrates the applicability of this methodology through a limited proof-of-concept application (the New Waddell Plant, a pumped hydroelectric energy storage facility in Phoenix, AZ). The beauty of our proposed framework lies in its ability to be imported and applied to any other pumped storage facility after accounting for site-specific features.

13 HYDRO ENERGY↗

NASA NTRS2012

An OSSE on Mesoscale Model Assimilation of Simulated HIRAD-Observed Hurricane Surface Winds

The hazards of landfalling hurricanes are well known, but progress on improving the intensity forecasts of these deadly storms at landfall has been slow. Many cite a lack of high-resolution data sets taken inside the core of a hurricane, and the lack of reliable measurements in extreme conditions near the surface of hurricanes, as possible reasons why even the most state-of-the-art forecasting models cannot seem to forecast intensity changes better. The Hurricane Imaging Radiometer (HIRAD) is a new airborne microwave remote sensor for observing hurricanes, and is operated and researched by NASA Marshall Space Flight Center in partnership with the NOAA Atlantic Oceanographic and Meteorological Laboratory/Hurricane Research Division, the University of Central Florida, the University of Michigan, and the University of Alabama in Huntsville. This instrument?s purpose is to study the wind field of a hurricane, specifically observing surface wind speeds and rain rates, in what has traditionally been the most difficult areas for other instruments to study; the high wind and heavy rain regions. Dr. T. N. Krishnamurti has studied various data assimilation techniques for hurricane and monsoon rain rates, and this study builds off of results obtained from utilizing his style of physical initializations of rainfall observations, but obtaining reliable observations in heavy rain regions has always presented trouble to our research of high-resolution rainfall forecasting. Reliable data from these regions at such a high resolution and wide swath as HIRAD provides is potentially very valuable to mesoscale forecasting of hurricane intensity. This study shows how the data assimilation technique of Ensemble Kalman Filtering (EnKF) in the Weather Research and Forecasting (WRF) model can be used to incorporate wind, and later rain rate, data into a mesoscale model forecast of hurricane intensity. The study makes use of an Observing System Simulation Experiment (OSSE) with a simulated HIRAD dataset sampled during a hurricane and uses EnKF to forecast the track and intensity prediction of the hurricane. Comparisons to truth and error metrics are used to assess the model?s forecast performance.

Albers, Cerese↗

DOE OSTI2023

Evaluation of Cathode Materials with Lithium-Metal Anodes: Baseline Performance and Protocol Standardization of Coin Cells

The collaborative evaluation of electrode materials across multiple research entities requires standardized electrochemical testing protocols to produce reliable, one-to-one comparisons between different systems of interest. Similar to the work done by Long et al. on protocol standardization for coin-cell testing with graphite anodes [J. Electrochem. Soc., 163, A2999, (2016)], here we introduce two standardized testing protocols designed to quickly evaluate important electrochemical properties of cathode materials using lithium-metal anodes. The two protocols measure kinetic and thermodynamic capacity losses, rate- and voltage-dependent cycling capacities, instabilities at high voltage and high cycling rate, and overpotentials at various states of charge. We then apply these protocols to four commercially available cathode materials to establish benchmark performance metrics that can be used to screen and evaluate new cathode materials.

25 ENERGY STORAGE↗

NASA NTRS1996

GRASP/Ada 95: Reverse Engineering Tools for Ada

The GRASP/Ada project (Graphical Representations of Algorithms, Structures, and Processes for Ada) has successfully created and prototyped an algorithmic level graphical representation for Ada software, the Control Structure Diagram (CSD), and a new visualization for a fine-grained complexity metric called the Complexity Profile Graph (CPG). By synchronizing the CSD and the CPG, the CSD view of control structure, nesting, and source code is directly linked to the corresponding visualization of statement level complexity in the CPG. GRASP has been integrated with GNAT, the GNU Ada 95 Translator to provide a comprehensive graphical user interface and development environment for Ada 95. The user may view, edit, print, and compile source code as a CSD with no discernible addition to storage or computational overhead. The primary impetus for creation of the CSD was to improve the comprehension efficiency of Ada software and, as a result, improve reliability and reduce costs. The emphasis has been on the automatic generation of the CSD from Ada 95 source code to support reverse engineering and maintenance. The CSD has the potential to replace traditional prettyprinted Ada source code. The current update has focused on the design and implementation of a new Motif compliant user interface, and a new CSD generator consisting of a tagger and renderer. The Complexity Profile Graph (CPG) is based on a set of functions that describes the context, content, and the scaling for complexity on a statement by statement basis. When combined graphicafly, the result is a composite profile of complexity for the program unit. Ongoing research includes the development and refinement of the associated functions, and the development of the CPG generator prototype. The current Version 5.0 prototype provides the capability for the user to generate CSDs and CPGs from Ada 95 source code in a reverse engineering as well as forward engineering mode with a level of flexibility suitable for practical application. This report provides an overview of the GRASP/Ada project with an emphasis on the current update.

Cross, James H., II↗

DOE OSTI2026

Enhancing Operational Safety via Agentic Dialogue Hazard Identification Analysis

Operational safety in high-stakes domains such as industrial process control, autonomous, and safety-critical systems demand reliable hazard identification. While large language models (LLMs) have shown promise in automating safety analysis tasks, single-turn, monolithic inference is brittle: it lacks the self-correction, deliberation, and contextual refinement that safety engineers apply iteratively. In this paper, we introduce HAZDIAL, a framework that investigates whether structured agentic dialogue (multi-agent, multi-turn interactions) improves the quality of NLP-based hazard identification over single-pass baselines. We systematically compare two dialogue modalities: adversarial debate and constructive discussion, and propose an genetic algorithm-based agentic interaction optimization. We evaluate all configurations against a curated golden dataset using standard classification metrics (accuracy, precision, recall, F1) and a novel dialogue metrics. This work advances the intersection of dialogue systems, multi-agent reasoning, and AI safety, providing empirical evidence for dialogue-driven hazard analysis.

Das, Sanjay [ORNL] (ORCID:0009000542591915)↗

DOE OSTI2025

Rapid Bayesian High Entropy Alloy Designs Fabricated via Wire Arc Additive Manufacturing

Purpose: This project seeks to demonstrate a new high-throughput (rapid) alloy design technique applied to creating new high entropy alloys (HEAs) for extreme environments. High entropy alloys shift the design paradigm from being focused on a single principal element (e.g. nickel-based alloys) to target alloys that include high atomic fractions (X >10%) of multiple elements. These HEA materials can exhibit sluggish diffusion and enhanced corrosion resistance, ideal for potential applications in advanced ultra supercritical (A-USC) steam cycles for power generation. Scope: The addition of multiple elements in high atomic fractions creates an enormous design space that cannot easily be investigated by traditional material design strategies such as designed of experiments (DOE). This project utilizes a Bayesian machine learning algorithm that has been modified to work with calculation of phase diagrams (CALPHAD) software. This Bayesian algorithm reduces manual inputs and increase the likelihood of achieving an optimal solution. Compositional inputs to this algorithm will be assessed using existing material property models for high temperature strength and corrosion resistance. The target for alloy performance will be a 15% (~100 ⁰C) increase in allowable service temperature beyond heat-resistant stainless steels while maintaining or improving alloy cost and corrosion resistance. Haynes 230 was selected as a baseline, which is 57 wt% Ni with 22 wt% Cr 14 wt% W, and 2 wt% Mo as solid solution strengtheners. In addition to rapid design via Bayesian machine learning, the alloys were rapidly fabricated using a multi-wire arc additive manufacturing (mWAAM) technique which allows for precise control of alloy composition and assessing of alloy design “windows” to study composition effects. Build speeds for wire-arc additive processes are among the highest for additive technologies enabling rapid and reliable sample fabrication when compared to conventional methods such as arc button melting. The mWAAM samples will be rapidly characterized via instrumented indentation for room temperature modulus and strength and for elevated temperature strength via hot hardness tests. After being screened with hardness testing, potential alloys will be further evaluated with conventional microscopy techniques including scanning electron microscopy (SEM) and transmission electron microscopy (TEM) to assess agreement with modeling results. The most promising compositions will also be evaluated by printing full sized tensile specimens for mechanical behavior tests at elevated temperatures. Results: Bayesian machine learning of a single performance function was initially used to optimize five performance metrics: 1) single phase stability, 2) yield strength, 3) creep resistance (low diffusion coefficient), 4) freezing range (weldability), and 5) material cost. The single performance function was suboptimal as assumptions had to be made about the results while formulating the optimization. A goal-oriented Bayesian optimization strategy (Hanaoka, 2021) was implemented with CALPHAD for use with the five metrics above. This multi-objective Bayesian optimization (MOBO) enabled the design of NiCrCoFe alloys with V and W additions. A base composition of NiCoCr was selected as Ni provides a stable FCC matrix, Cr aids corrosion/oxidation resistance, and Co is a solid-solutions strengthener that also improves creep by increasing the activation energy. Fe helps reduce diffusion coefficients and cost. Finally, V and W were selected for their reasonable solubility and high atomic misfit to aid in solid solution strengthening. Cracking of the mWAAM specimens was an early issue, and the Easton solidification cracking model (Easton et al., 2014a) was selected for addition to the MOBO function. High performing alloys fabricated by mWAAM included Ni 28 Cr 25 Co 26 Fe 15 V 8 and Ni 62 Cr 18 Co 1 Fe 3 W 15 . It was observed that even after adapting the mWAAM process for W, the W did not fully dissolve. To fully evaluate the Ni 62 Cr 18 Co 1 Fe 3 W 15 composition, a cored wire (80-20 NiCr sheath/powder core) was manufactured and printed via WAAM, and HIP’ing was utilized to homogenize and densify the printed alloy. The V and W alloys produced met metrics 1 (solid solution), 4 (solidification cracking), and 5 (cost). However, an unmodeled mechanism of thermal stress cracking was identified in the WAAM produced materials, perhaps exacerbated by the lack of grain boundary strengthening elements (B, C). Conclusions & Recommendations: A high-throughput (rapid) alloy design technique was applied to designing and manufacturing new high entropy alloys (HEAs) for extreme environments utilizing MOBO and mWAAM. The developed process was rapid and effective in addressing the mechanisms included in the model. The lack of grain boundary strengthening element additions (e.g., B, C) was a simplification that likely produced thermal stress cracking that turned into a large part of the investigation. Additions on the order of 0.005 wt% B and 0.05 wt% C likely would have minimized thermal stress grain boundary cracking. Overall, the high throughput design strategy is promising for rapid design of metrics-driven alloys for advanced ultra supercritical (A-USC) steam cycles for power generation. The MOBO and mWAAM process could be commercialized to accelerate metrics-driven alloy design. In addition, the cored-wire process utilized for scale-up is a promising high-volume process for WAAM alloy development and scale-up.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Near-term Persistent Platform Orbital Testbed: Three Candidate Architecture Options

On-orbit Servicing, Assembly, and Manufacturing (OSAM) will revolutionize the space industry by transforming the concept of operations of space systems and enabling new, radically different system implementations. These new implementations will benefit from a novel persistent asset design paradigm which focuses on evolvable designs that are tailored to the operational environment, not the launch environment. In addition, the ability to launch sub-systems independently enable future persistent assets to economically expand in capability and size, achieving cost effective and productive operations lasting for decades like terrestrial observatories. With few exceptions (International Space Station, Hubble Space Telescope, Mission Extension Vehicle customers), current space systems are not visited once they are operational. Leveraging emerging low cost commercial launch provides the ability to repeatedly and routinely revisit space systems. Thus, revolutionary new approaches for space system design are possible, creating completely new opportunities for small businesses and accelerating the growth of already established space industries. To usher in the revolutionary new operational paradigm, two things are needed. First, to build confidence in the technology and new paradigm, there must be a leading example, a bellwether persistent asset, that demonstrates the reliability and maturity of the new persistent asset paradigm (where repeated visits are common). Second, in order to rapidly advance and validate OSAM capabilities, an efficient means is required to conduct tests in the space environment. A persistent platform testbed satisfies both these needs. The space environment exhibits a plethora of characteristics that are difficult and costly to accurately simulate for a full system in a terrestrial laboratory, such as near zero gravity, a wide range of ionizing radiation types, atomic oxygen, and micro-meteoroids and space debris traveling at high velocity. In addition, since persistent assets range in mass from a few grams to several metric tons, it is difficult to accurately simulate interactions between these systems and visiting vehicles (that also exhibit a wide range of varying masses and capabilities). These interactions include the transmission of forces and/or exchanging mass (in the form of instruments, fuel, robotic assets, etc.). Thus, a rapid, versatile and cost efficient in-space testing capability that includes a persistent test platform and a surrounding in-space test zone is needed to mature technologies through experimentation. The testbed can provide common services, such as: power, thermal control, vibration isolation, data transmission between experiments and terrestrial experimenters, station-keeping, pointing, and robotic agents that can be leveraged by customer experiments. The onboard robotic agents can be used to provide payload handling services, such as: assembly, change out or upgrade, relocation, connecting/disconnecting utilities, inspection, repair or servicing, etc. Since the persistent platform cost will be amortized over many hosted payloads, its services can eventually be offered at a price much lower than if one were to design a unique and dedicated spacecraft and mission for those few experiments. The key to achieving an effective testbed is providing efficient cost effective access and infrastructure to a variety of commercial, academic and government customers coupled with extensibility, in the capability of an individual persistent platform test bed or replication of the test bed in a different operational regime. Three potential options for implementing a test bed were developed and evaluated in this study.

Persistent Platform↗

NASA NTRSDate not supplied

Near-term Persistent Platform Orbital Testbed: Three Candidate Architecture Options

Persistent Platform↗

NASA NTRS1984

An experimental evaluation of the Sternberg task as a workload metric for helicopter Flight Handling Qualities (FHQ) research

The objective was to determine whether the Sternberg item-recognition task, employed as a secondary task measure of spare mental capacity for flight handling qualities (FHQ) simulation research, could help to differentiate between different flight-control conditions. FHQ evaluations were conducted on the Vertical Motion Simulator at Ames Research Center to investigate different primary flight-control configurations, and selected stability and control augmentation levels for helicopters engaged in low-level flight regimes. The Sternberg task was superimposed upon the primary flight-control task in a balanced experimental design. The results of parametric statistical analysis of Sternberg secondary task data failed to support the continued use of this task as a measure of pilot workload. In addition to the secondary task, subjects provided Cooper-Harper pilot ratings (CHPR) and responded to workload questionnaire. The CHPR data also failed to provide reliable statistical discrimination between FHQ treatment conditions; some insight into the behavior of the secondary task was gained from the workload questionnaire data.

Hemingway, J. C.↗

NASA NTRS1984

The Sternberg Task as a Workload Metric in Flight Handling Qualities Research

The objective of this research was to determine whether the Sternberg item-recognition task, employed as a secondary task measure of spare mental capacity for flight handling qualities (FHQ) simulation research, could help to differentiate between different flight-control conditions. FHQ evaluations were conducted on the Vertical Motion Simulator at Ames Research Center to investigate different primary flight-control configurations, and selected stability and control augmentation levels for helicopers engaged in low-level flight regimes. The Sternberg task was superimposed upon the primary flight-control task in a balanced experimental design. The results of parametric statistical analysis of Sternberg secondary task data failed to support the continued use of this task as a measure of pilot workload. In addition to the secondary task, subjects provided Cooper-Harper pilot ratings (CHPR) and responded to a workload questionnaire. The CHPR data also failed to provide reliable statistical discrimination between FHQ treatment conditions; some insight into the behavior of the secondary task was gained from the workload questionnaire data.

Hemingway, J. C.↗

DOE OSTI2024

Distribution Grid Impact Study in Highland Park, Michigan: Understanding Rooftop Solar, Behind-the-Meter Energy Storage, Electric Vehicle Charging, and Building Electrification [Slides]

Through the Communities LEAP (Local Energy Action Program) Pilot, the National Renewable Energy Laboratory (NREL) engaged the Highland Park Stakeholder Coalition to scope four technical assistance work areas to address their energy needs and goals. This slide deck addresses the highlighted tasks under work area "B" related to policy analysis, due diligence, and case studies for removing barriers and providing best practices for local clean energy development. Highland Park community members face frequent, long-duration power interruptions due largely to the aging distribution system serving the area and the legacy design standards used in its construction. While degrading physical infrastructure such as poles, crossarms, and transformers can result in this substandard reliability, another notable characteristic of this legacy system is the lower, 4.8 kV, voltage class. This is a legacy construction standard which many utilities, DTE included, are phasing out in favor of higher, 15 or 25 kV, voltage classes instead. The existing 4.8 kV distribution system serving Highland Park may limit significant adoptions of clean-energy technologies like high percentages of building electrification or electric vehicle adoption. The following analysis seeks to quantify these limitations under a variety of clean-energy technology adoption scenarios. It compares the overall system risks of the present system to those of a hypothetical, upgraded 13.2 kV system, using NREL-developed risk metrics and offers upgrade cost considerations. The legacy 4.8 kV voltage class serving Highland park is not, as we have modeled it, a major limitation to the widespread adoption of cost-optimal rooftop solar and/or behind-the-meter energy storage. Within our modeling framework, these technologies namely impact secondary, low-voltage assets, which may be remedied without the need for a system-wide upgrade to a 13.2 kV voltage class. Our model of the current 4.8kV system indicates it is not capable of supporting community-wide electrification efforts. Widespread building electrification, and the resulting large increase in wintertime load, dramatically increases the prevalence of voltage violations and thermal overloading on the current 4.8 kV distribution system. These impacts illustrate the need for system-wide upgrades to a 13.2 kV voltage class to accommodate these technologies. Low to Moderate DER adoption does not adversely impact the grid but does improve undervoltage and asset overloading issues. However, these benefits are insufficient to defer grid upgrades. Higher DER penetration is shown to increase overvoltage and asset overloading in future electrification scenarios.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗