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At least 343 records · Page 19

Performability modeling based on real data: A case study

Described is a measurement-based performability model based on error and resource usage data collected on a multiprocessor system. A method for identifying the model structure is introduced and the resulting model is validated against real data. Model development from the collection of raw data to the estimation of the expected reward is described. Both normal and error behavior of the system are characterized. The measured data show that the holding times in key operational and error states are not simple exponentials and that a semi-Markov process is necessary to model system behavior. A reward function, based on the service rate and the error rate in each state, is then defined in order to estimate the performability of the system and to depict the cost of apparent types of errors.

Hsueh, M. C.↗

Minimum Energy Routing through Interactive Techniques (MERIT) modeling

The MERIT program is designed to demonstrate the feasibility of fuel savings by airlines through improved route selection using wind observations from their own fleet. After a discussion of weather and aircraft data, manually correcting wind fields, automatic corrections to wind fields, and short-range prediction models, it is concluded that improvements in wind information are possible if a system is developed for analyzing wind observations and correcting the forecasts made by the major models. One data handling system, McIDAS, can easily collect and display wind observations and model forecasts. Changing the wind forecasts beyond the time of the most recent observations is more difficult; an Australian Mesoscale Model was tested with promising but not definitive results.

Wylie, Donald P.↗

NASA C-17 Usage Overview

The usage and integrated vehicle health management of the NASA C-17. Propulsion health management flight objectives for the aircraft include mapping of the High Pressure Compressor in order to calibrate a Pratt and Whitney engine model and the fusion of data collected from existing sensors and signals to develop models, analysis methods and information fusion algorithms. An additional health manage flight objective is to demonstrate that the Commercial Modular Aero-Propulsion Systems Simulation engine model can successfully execute in real time onboard the C-17 T-1 aircraft using engine and aircraft flight data as inputs. Future work will address aircraft durability and aging, airframe health management, and propulsion health management research in the areas of gas path and engine vibration.

Miller, Christopher R.↗

Experimental validation of a co-simulation architecture for modeling whole-building and detailed electrical distribution performance

This article presents an experimental validation of a co-simulation architecture for simultaneously modeling whole-building energy performance and detailed building electrical distribution system performance. The co-simulation architecture consists of a whole-building energy model (EnergyPlus®) embedded within a Modelica-based building electrical distribution system library called the Building Electrical Efficiency Analysis Model (BEEAM) using the Functional Mock-up Interface standard. We validate the model using experimental data collected at a full-scale test cell within Lawrence Berkeley National Laboratory’s FLEXLAB® facility. In conclusion, we show that the co-simulation model accurately predicts the electrical, mechanical, and thermal performance of the test cell for typical loads with both an AC and a DC electrical distribution topology.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

The Wallops Flight Facility Rapid Response Range Operations Initiative

While the dominant focus on short response missions has appropriately centered on the launch vehicle and spacecraft, often overlooked or afterthought phases of these missions have been launch site operations and the activities of launch range organizations. Throughout the history of organized spaceflight, launch ranges have been the bane of flight programs as the source of expense, schedule delays, and seemingly endless requirements. Launch Ranges provide three basic functions: (1) provide an appropriate geographical location to meet orbital other mission trajectory requirements, (2) provide project services such as processing facilities, launch complexes, tracking and data services, and expendable products, and (3) assure safety and property protection to participating personnel and third-parties. The challenge with which launch site authorities continuously struggle, is the inherent conflict arising from projects whose singular concern is execution of their mission, and the range s need to support numerous simultaneous customers. So, while tasks carried out by a launch range committed to a single mission pale in comparison to efforts of a launch vehicle or spacecraft provider and could normally be carried out in a matter of weeks, major launch sites have dozens of active projects separate sponsoring organizations. Accommodating the numerous tasks associated with each mission, when hardware failures, weather, maintenance requirements, and other factors constantly conspire against the range resource schedulers, make the launch range as significant an impediment to responsive missions as launch vehicles and their cargo. The obvious solution to the launch site challenge was implemented years ago when the Department of Defense simply established dedicated infrastructure and personnel to dedicated missions, namely an Inter Continental Ballistic Missile. This however proves to be prohibitively expensive for all but the most urgent of applications. So the challenge becomes how can a launch site provide acceptably responsive mission services to a particular customer without dedicating extensive resources and while continuing to serve other projects? NASA's Wallops Flight Facility (WFF) is pursuing solutions to exactly this challenge. NASA, in partnership with the Virginia Commercial Space Flight Authority, has initiated the Rapid Response Range Operations Initiative (R3Ops). R3Ops is a multi-phased effort to incrementally establish and demonstrate increasingly responsive launch operations, with an ultimate goal of providing ELV-class services in a maximum of 7-10 days from initial notification routinely, and shorter schedules possible with committed resources. This target will be pursued within the reality of simultaneous concurrent programs, and ideally, largely independent of specialized flight system configurations. WFF has recently completed Phase 1 of R3Ops, an in-depth collection (through extensive expert interviews) and software modeling of individual steps by various range disciplines. This modeling is now being used to identify existing inefficiencies in current procedures, to identify bottlenecks, and show interdependencies. Existing practices are being tracked to provide a baseline to benchmark against as new procedures are implemented. This paper will describe in detail the philosophies behind WFF's R3Ops, the data collected and modeled in Phase 1, and strategies for meeting responsive launch requirements in a multi-user range environment planned for subsequent phases of this initiative.

Underwood, Bruce E.↗

Dynamic Modeling of a Kaplan Hydroturbine Using Optimal Parametric Tuning and Real Plant Operational Data

To address grid variability caused by renewable energy integration and to maintain grid reliability and resilience, hydropower must quickly adjust its power generation over short time periods. This changing energy generation landscape requires advance technology integration and adaptive parameter optimization for hydropower systems via digital twin effort. However, this is difficult owing to the lack of characterization and modeling for the nonlinear nature of hydroturbines. To solve this issue, this paper first formulates a six-coefficient Kaplan hydroturbine model and then proposes a parametric optimization tuning framework based on the Nelder–Mead algorithm for adaptive dynamic learning of the six-coefficients so as to build models that describe the turbine. To assess the performance of the proposed optimal parametric tuning technique, operational data from a real-world Kaplan hydroturbine unit are collected and used to model the relationship between the gate opening and the generated power production. The findings show that the proposed technique can effectively and adaptively learn the unknown dynamics of the Kaplan hydroturbine while optimally tune the unknown coefficients to match the generated power output from the real hydroturbine unit with an inaccuracy of less than 5%. The method can be used to provides optimal tuning of parameters critical for controller design, operational optimization and daily maintenance for hydroturbines in general.

13 HYDRO ENERGY↗

The Pursuit of K: Reflections on the Current State-of-the-Art in Stress Intensity Factor Solutions for Practical Aerospace Applications

The elastic stress intensity factor (SIF, commonly denoted as K) is the foundation of practical fracture mechanics (FM) analysis for aircraft structures. This single parameter describes the first-order effects of stress magnitude and distribution as well as the geometry of both structure/component and crack. Hence, the calculation of K is often the most significant step in fatigue analysis based on FM. This presentation will provide several reflections on the current state-of-the-art in SIF solution methods used for practical aerospace applications, including a brief historical perspective, descriptions of some recent and ongoing advances, and comments on some remaining challenges. Newman and Raju made significant early contributions to practical structural analysis by developing closed-form SIF equations for surface and corner cracks in simplified geometries, often based on empirical fits of finite element (FE) solutions. Those solutions (and others like them) were sometimes revised as new analyses were conducted or limitations discovered. The foundational solutions have exhibited striking longevity, despite the relatively "coarse" FE models employed many decades ago. However, in recent years, the accumulation of different generations of solutions for the same nominal geometry has led to some confusion (which solution is correct?), and steady increases in computational capabilities have facilitated the discovery of inaccuracies in some (not all!) of the legacy solutions. Some examples of problems and solutions are presented and discussed, including the challenge of maintaining consistency with legacy design applications. As computational power has increased, the prospect of calculating large numbers of SIF solutions for specific complex geometries with advanced numerical methods has grown more attractive. Fawaz and Andersson, for example, have been generating literally millions of new SIF solutions for different combinations of multiple cracks under simplified loading schemes using p-version FE methods. These data are invaluable, but questions remain about their practical use, because the tabular databases of key results needed to support practical life analysis can occupy gigabytes of storage for only a few classes of geometries. The prospect of using such advanced numerical methods to calculate in real time only those K solutions actually needed to support a specific crack growth analysis is also tempting, but the stark reality is that the computational cost is still so high that the approach is not practical except for specific, critical application problems. Some thoughts are offered about alternative paradigms. Compounding approaches are some of the earliest building blocks of SIF development for more complex geometries. These approaches are especially attractive because of their very low computational cost and their conceptual robustness; they are, in some ways, an intriguing contrast and complement to the brute-force numerical methods. In recent years, researchers at NRC-Canada have published remarkable results showing how compounding approaches can be used to generate accurate solutions for very difficult problems. Examples are provided of some successes--and some limitations--using this approach. These closed-form, tabulated numerical, and compounding approaches have typically been used for simple remote loading with simple load paths to the crack. However, many significant cracks occur in complex stress gradient fields. This is a job for weight function (WF) methods, where the arbitrary stress distribution on the crack plane in the corresponding uncracked body (typically determined using FE methods) is used to determine K. Several significant recent advances in WF methods and solutions are highlighted here. Fueled by advanced 3D numerical methods, many new solutions have been generated for classic geometries such as surface and corner cracks with wide ranges of geometrical validity. A new WF formulation has also be developed for part-through cracks considering the arbitrary stress gradients in all directions in the crack plane (so-called bivariant solutions). Basic WF methods have recently been combined with analytical expressions for crack plane stresses to develop a large family of accurate SIF solutions for corner, surface, and through cracks at internal or external notches with very wide ranges of shapes, sizes, acuities, and offsets. Finally, WF solutions are much faster than FE or boundary element solutions, but can still be much slower than simple closed-form solutions, especially for bivariant solutions that can require 2D numerical integration. Novel pre-integration and dynamic tabular methods have been developed that substantially increase the speed of these advanced WF solutions. The practical utility of advanced SIF methods, including both WF and direct numerical methods, is greatly enhanced if the FM life analysis can be directly and efficiently linked with digital models of the actual structure or component (e.g., FE models for stress analysis). Two recent advances of this type will be described. One approach directly interfaces the FM life analysis with the FE model of the uncracked component (including stress results). Through a powerful graphical user interface, simplified FM life models can be constructed (and visualized) directly on the component model, with the computer collecting the geometry and stress gradient information needed for the life calculation. An even more powerful paradigm uses expert logic to automatically build an optimum simple fracture model at any and every desired location in the component model, perform the life calculation, and even generate fatigue crack growth life contour maps, all with minimal user intervention. This paradigm has also been extended to the automatic calculation of fracture risk, considering uncertainty or variability in key input parameters such as initial crack size or location. Another new integrated approach links the engineering life analysis, the component model, and a 3D numerical fracture analysis built with the same component model to generate a table of SIF values at a specific location that can then be employed efficiently to perform the life calculation. Some attention must be given to verification and validation (V&V) issues and challenges: how good are these SIF solutions, how good is good enough, and does anyone believe the life answer? It is important to think critically about the different sources of error or uncertainty and to perform V&V in a hierarchal, building-block manner. Some accuracy issues for SIF solutions, for example, may actually involve independent material behavior issues, such as constraint loss effects for crack fronts near component surfaces, and can be a source of confusion. Recommendations are proposed for improved V&V approaches. This presentation will briefly but critically survey the range of issues and advances mentioned above, with a particular view towards assembling an integrated approach that combines different methods to create practical tools for real-world design and analysis problems. Examples will be selectively drawn from the recent literature, from recent enhancements in the NASGRO and DARWIN computer codes, and from previously unpublished research

CraigMcClung, R.↗

A Koopman-based residual modeling approach for the control of a soft robot arm

Soft robots are challenging to model and control due to their poorly defined kinematics and nonlinear dynamics. Recently, Koopman operator theory has been shown capable of constructing control-oriented soft robot models from data. However, building these models requires extensive data collection and they do not necessarily generalize well outside of the training observations. This paper presents a more data-efficient and generalizable approach to soft robot modeling that first identifies a physics-based Koopman model then supplements it with a data-driven residual Koopman model. The resulting combined model is linear and thus compatible with real-time model-based control techniques such as Model Predictive Control (MPC). The efficacy of the approach is demonstrated on several simulated systems and on a real soft robot arm, where it is shown to generate models that are more accurate than purely physics-based models and require less data to construct than purely data-driven models. Using a model-based controller, the soft arm is able to successfully track end effector trajectories, perform a pick-and-place task, and write on a dry-erase board, showcasing the applicability of this framework to increase the capabilities of soft robotic systems.

Daniel Bruder↗

A feasibility study of using remotely sensed data for water resource models

Remotely sensed data were collected to demonstrate the feasibility of applying the results to water resource problems. Photographs of the Wolf Creek watershed in southwestern Colorado were collected over a one year period. Cloud top temperatures were measured using a radiometer. Thermal imagery of the Wolf Creek Pass area was obtained during one pre-dawn flight. Remote sensing studies of water resource problems for user agencies were also conducted. The results indicated that: (1) remote sensing techniques could be used to assist in the solution of water resource problems; (2) photogrammetric determination of snow depths is feasible; (3) changes in turbidity or suspended material concentration can be observed; and (4) surface turbulence can be related to bed scour; and (5) thermal effluents into rivers can be monitored.

Ruff, J. F.↗

A measurement-based performability model for a multiprocessor system

A measurement-based performability model based on real error-data collected on a multiprocessor system is described. Model development from the raw errror-data to the estimation of cumulative reward is described. Both normal and failure behavior of the system are characterized. The measured data show that the holding times in key operational and failure states are not simple exponential and that semi-Markov process is necessary to model the system behavior. A reward function, based on the service rate and the error rate in each state, is then defined in order to estimate the performability of the system and to depict the cost of different failure types and recovery procedures.

Ilsueh, M. C.↗

Human Thermal Model Evaluation Using the JSC Human Thermal Database

The human thermal database developed at the Johnson Space Center (JSC) is used to evaluate a set of widely used human thermal models. This database will facilitate a more accurate evaluation of human thermoregulatory response using in a variety of situations, including those situations that might otherwise prove too dangerous for actual testing--such as extreme hot or cold splashdown conditions. This set includes the Wissler human thermal model, a model that has been widely used to predict the human thermoregulatory response to a variety of cold and hot environments. These models are statistically compared to the current database, which contains experiments of human subjects primarily in air from a literature survey ranging between 1953 and 2004 and from a suited experiment recently performed by the authors, for a quantitative study of relative strength and predictive quality of the models. Human thermal modeling has considerable long term utility to human space flight. Such models provide a tool to predict crew survivability in support of vehicle design and to evaluate crew response in untested environments. It is to the benefit of any such model not only to collect relevant experimental data to correlate it against, but also to maintain an experimental standard or benchmark for future development in a readily and rapidly searchable and software accessible format. The Human thermal database project is intended to do just so; to collect relevant data from literature and experimentation and to store the data in a database structure for immediate and future use as a benchmark to judge human thermal models against, in identifying model strengths and weakness, to support model development and improve correlation, and to statistically quantify a model s predictive quality.

Cognata, T.↗

Human Thermal Model Evaluation Using the JSC Human Thermal Database

Human thermal modeling has considerable long term utility to human space flight. Such models provide a tool to predict crew survivability in support of vehicle design and to evaluate crew response in untested space environments. It is to the benefit of any such model not only to collect relevant experimental data to correlate it against, but also to maintain an experimental standard or benchmark for future development in a readily and rapidly searchable and software accessible format. The Human thermal database project is intended to do just so; to collect relevant data from literature and experimentation and to store the data in a database structure for immediate and future use as a benchmark to judge human thermal models against, in identifying model strengths and weakness, to support model development and improve correlation, and to statistically quantify a model s predictive quality. The human thermal database developed at the Johnson Space Center (JSC) is intended to evaluate a set of widely used human thermal models. This set includes the Wissler human thermal model, a model that has been widely used to predict the human thermoregulatory response to a variety of cold and hot environments. These models are statistically compared to the current database, which contains experiments of human subjects primarily in air from a literature survey ranging between 1953 and 2004 and from a suited experiment recently performed by the authors, for a quantitative study of relative strength and predictive quality of the models.

Bue, Grant↗

Advances in Entry Systems Modeling: Modeling Summer Visit 2025 Technical Reports

This NASA Technical Memorandum presents the collective work carried out during the Modeling Summer Visit (MSV) 2025, a collaborative research program between NASA Ames Research Center and three leading European research institutions: the University of Bordeaux, the von Karman Institute (VKI), and Ecole Polytechnique. Held from July 7th to August 1st, 2025, the NASA ARC MSV program brought together 42 researchers from Europe to work alongside NASA staff on 22 projects in entry systems modeling. The program was organized by Bruno Dias, Sergio Fraile-Izquierdo, and Jeremie Meurisse from Analytical Mechanics Associates, Inc., in collaboration with Marc Massot (Ecole Polytechnique), Jean Lachaud (University of Bordeaux), and Thierry Magin (VKI). The MSV program traces its origins to an initiative started by Nagi N. Mansour in 2018, with this 2025 edition representing a consolidation and expansion of that original vision. The projects were organized into six thematic groups: Porous Media, Numerical Methods, Plasma/Rarefied Methods, Experimental Reconstruction, Flow and Material Coupling Methods, and Transition and High-Speed Flows. Throughout the four-week program, participants presented their work in three public presentations (July 7th, July 21st, and August 1st), allowing for continuous feedback and discussion of their evolving research.

Plasmas↗

Applying Transfer Learning for Street-Scale Nuisance Flood Forecasting in Coastal-Urban Cities

An important challenge with Machine Learning (ML) is its transferability; that is, whether a ML model trained on one set of data can be applied to a second set of data without requiring a full re-training of the model. Transfer Learning (TL) addresses this challenge by transferring knowledge learned in the source domain (the data it was trained on) to the target domain (a second set of data that is statistically different but related, which the model was not trained on). This study investigates the use of TL for street-scale nuisance flood forecasting by exploring whether a ML model trained on data collected for one set of streets can effectively forecast flooding for another set of streets in the same city using TL. The envisioned use case is a city deploying a new flood depth monitoring sensor on a street and using TL to apply a ML model, trained on sensor data from an existing flood depth sensor network, to this new street. Eventually, the new flood depth sensor will have a sufficient dataset for training its own ML model, but TL can be used to fill the gap in time while this new dataset is being generated. This method is explored using a Long Short-Term Memory (LSTM) model trained on data for the flood-prone streets of Norfolk City, Virginia. The data used for training includes environmental time series (rainfall, tide), topographic features (Digital Elevation Model (DEM), Topographic Wetness Index (TWI), Depth To Water (DTW)), and street-scale flood depth time series obtained from a high-fidelity physics-based model, acting as a synthetic street-scale stream depth sensor dataset since actual stream depth sensor data is generally unavailable for most cities. A set of 180 flood-prone streets was used to train a base model, while another set of 180 flood-prone streets was used to re-train that model using different TL strategies. The results show that full-weight re-training proved most effective and minimal re-training of only the output layer was insufficient. The advantage of TL was most pronounced when target data was limited, meaning data collected at the new water depth sensor location included generally less than 18 flood events. As target data increased beyond 18 flood events, the benefit of TL diminished relative to training a ML model directly on the local flood events. These findings can assist cities as they implement street-scale flood sensing systems to create accurate forecasts for new sensing locations that do not yet have sufficient data records to train a local ML model.

Roy, Binata [Univ. of Virginia, Charlottesville, V↗

Positional Dependence of SNPP VIIRS Solar Diffuser BRDF Change Factor: An Empirical Approach

The Earth-observing Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership satellite regularly performs on-orbit radiometric calibration of its reflective solar bands (RSBs), primarily through observations of an onboard sunlit solar diffuser (SD). The on-orbit change of the SD bidirectional reflectance distribution function (BRDF) value, quantified by a numerical factor called the H-factor, is determined by the onboard SD stability monitor. Our previous study showed that the H-factor is solar angle and view direction dependent. In this study, we determine the dependence of the H-factor on the detector SD view footprint location. We fit an empirical model to the NASA Collection 1 SNPP VIIRS Level 1B (L1B) spectral reflectance difference across the detectors in an RSB over uniform Earth scenes of the Libya 4 desert and deep convective clouds. We apply the model predicted SD positional dependent H-factor to calibrate the RSBs. Under this new calibration scheme, the original unreal striping is removed from the homogeneous Libya 4 desert and the deep convective cloud images, as well as the original unreal striping from the Dunhuang desert image. The SD positional dependent H-factor has been used to calculate the SNPP VIIRS RSB radiometric correction factor for the NASA Collection 2.0 SNPP VIIRS L1B products.

SNPP VIIRS↗

Development of a Human Motor Model for the Evaluation of an Integrated Alerting and Notification Flight Deck System

A human motor model was developed on the basis of performance data that was collected in a flight simulator. The motor model is under consideration as one component of a virtual pilot model for the evaluation of NextGen crew alerting and notification systems in flight decks. This model may be used in a digital Monte Carlo simulation to compare flight deck layout design alternatives. The virtual pilot model is being developed as part of a NASA project to evaluate multiple crews alerting and notification flight deck configurations. Model parameters were derived from empirical distributions of pilot data collected in a flight simulator experiment. The goal of this model is to simulate pilot motor performance in the approach-to-landing task. The unique challenges associated with modeling the complex dynamics of humans interacting with the cockpit environment are discussed, along with the current state and future direction of the model.

Daiker, Ron↗

Predicting Damages to Remainder Parcels in Right-of-Way Acquisitions for Expanding Transportation Infrastructure: Using a Truncated Finite-Mixture Model

Right-of-way acquisition is a critical component of transportation infrastructure development. Transportation infrastructure projects cannot proceed without proper right-of-way acquisition or may face significant delays. State Departments of Transportation frequently acquire parcels of land for roadway expansion projects. A majority of these acquisitions can be partial takings, referring to a portion of a parcel that is acquired. The remainder of the property usually suffers economic changes due to the partial acquisition, which can be calculated as damage percentages. The damage percentage represents the extent to which the remaining land or property value has been diminished due to the acquisition. It reflects the remaining property value percentage that may have been lost or compromised due to the acquisition. Here, this study aims to provide a robust model to estimate damage percentages to the remainder parcels that may help state Departments of Transportation appraisers make early predictions about the damages in cases involving partial takings. The research uses 509 appraisal reports from the Tennessee Department of Transportation to identify the key parcel attributes that influence the percentage of damages. Three regression models are developed: a linear regression model, a finite-mixture model (FMM), and a truncated FMM with two latent classes. The modeling results show that the truncated FMM with two classes outperforms the other models. To validate the models, actual sales data is collected and analyzed for 59 properties, and the results suggest that the model predictions are fairly accurate. A predictive tool is developed based on the models to help appraisers anticipate right-of-way damages under different scenarios and can provide early predictions about the damages.

42 ENGINEERING↗

Airframe Noise Sub-Component Definition and Model

Both in-house, and jointly with NASA under the Advanced Subsonic Transport (AST) program, Boeing Commerical Aircraft Company (BCA) had begun work on systematically identifying specific components of noise responsible for total airframe noise generation and applying the knowledge gained towards the creation of a model for airframe noise prediction. This report documents the continuation of the collection of database from model-scale and full-scale airframe noise measurements to compliment the earlier existing databases, the development of the subcomponent models and the generation of a new empirical prediction code. The airframe subcomponent data includes measurements from aircraft ranging in size from a Boeing 737 to aircraft larger than a Boeing 747 aircraft. These results provide the continuity to evaluate the technology developed under the AST program consistent with the guidelines set forth in NASA CR-198298.

Golub, Robert A.↗