Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “approach”

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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

A Scenario-Based Approach to Assess Continuity Gaps in Earth Observations

Decision analysis processes outlined in systems engineering references, such as the Systems Engineering Body of Knowledge [1] or the NASA Systems Engineering Handbook [2], recommend following a series of steps to support decision-making for engineering applications. These steps are consistent across the literature and typically involve defining objectives, defining relevant criteria against which candidate alternatives can be assessed, selecting an evaluation method, assessing alternatives, and making a recommendation based on this assessment. These approaches are well-suited to assess systems for which sets of common objectives and constraints can be identified. A vast body of literature describes their application to numerous engineering problems, and many methods have been developed since the middle of the 20th century to support the assessment of candidate alternatives for such systems [3, 4, 5, 6]. These approaches, however, show some limitations when decisions pertain to systems of systems. These collections of individual systems typically do not share a common set of objectives and constraints, tend to be highly complex, and the definition of assessable, high-value candidate alternatives poses a challenge due to interdependencies. The formulation, development, operation, and funding of Earth observing missions are such that gaps may occur between missions, therefore impacting the continuity of measurements. These Earth observing mission architectures constitute systems of systems for which a common set of objectives and constraints can be challenging to define. When tasked with assessing gaps that may occur for a series of spaceborne missions that address similar science parameters, the authors therefore proposed to depart from the traditional objective- and criteria-based approach and instead adopted a scenario-based approach. This approach does not require a prioritized set of common objectives; rather, it assesses the impact of possible decisions on the system-of-systems and characterizes its possible future states. It also offers the flexibility to adjust assumptions, update inputs, and refine supporting models over time, while enabling the rapid, early identification of challenges and key decision points. By simulating the impact of potential decisions on the entirety of the system-of-systems, the approach enables the synchronization of multiple decisions that typically occur at the level of the individual system. This paper provides an overview of the approach that was developed to assess continuity gaps for a series of operational and planned spaceborne Earth observing missions, a description of its application to the problem at hand, and a discussion of currently known limitations.

scenario earth observations continuity gaps↗
NASA NTRSDate not supplied

Hybrid Approaches to Systems Health Management and Prognostics

To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision making. In principle, data driven approaches can replace expensive experimental test-setups as well as reduce the number of simulations needed to explore, e.g., the parametric space of a multi-parameter model. Nonetheless, the limitations of pure data-driven methods came to light rather quickly, at least for some industries. In many industrial applications, data acquisition is costly, and the volume of data that can be collected does not satisfy the requirements for an effective model training and cross-validation. Therefore, some recent works in the area of machine learning is focusing on blending physics with data-driven algorithms, thus mitigating the drawbacks of the two approaches and emphasizing respective advantages. Partial physical knowledge of the problem can aid the learning process by “guiding” the algorithm towards efficient solutions that satisfy the physics driving the system behavior. The result is a hybrid modeling approach combining physical knowledge as well data driven methods to develop a unified hybrid approach. A hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Systems Health Management↗
NASA NTRS2022

Hybrid Model Based Approaches for Systems Health Management and Prognostics

This is a previously approved and published presentation. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Present achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision-making. In principle, data-driven approaches can replace expensive experimental test-setups as well as reduce the number of simulations needed to explore, e.g., the parametric space of a multi-parameter model. Nonetheless, the limitations of pure data-driven methods came to light rather quickly, at least for some industries. In many industrial applications, data acquisition is costly, and the volume of data that can be collected does not satisfy the requirements for effective model training and cross-validation. Therefore, some recent works in the area of machine learning is focusing on blending physics with data-driven algorithms, thus mitigating the drawbacks of the two approaches and emphasizing respective advantages. Partial physical knowledge of the problem can aid the learning process by “guiding” the algorithm towards efficient solutions that satisfy the physics driving the system behavior. The result is a hybrid modeling approach combining physical knowledge as well data-driven methods to develop a unified hybrid approach. A hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety-critical systems is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Prognostics↗
DOE OSTI2025

Differentiable hybrid neural network approach for enhancing reactor dynamics simulations

Reactor dynamics simulations provide essential insights into the time-dependent behavior of nuclear reactors under various operating conditions. However, high-fidelity simulations can be computationally intensive, requiring significant computational resources. Here, to address this challenge, this study employs a differentiable hybrid model that utilizes neural networks as a corrector to enhance the performance of a low-fidelity simulation, aligning its predictions with those of a high-fidelity simulation. Low-fidelity and high-fidelity simulations were obtained by adjusting the mesh size in the System Dynamics Analysis Tool. The differentiable hybrid model was trained in two approaches: time-step-wise and sequence-wise. It was then applied to simulate various transients in a molten salt reactor. Its performance was evaluated by comparing its responses to transients against those of the high-fidelity simulation. An additional approach was performed using a data-driven model to correct the low-fidelity simulation. In comparison, the differentiable hybrid model showed significant improvements in transient prediction, effectively addressing the limitations of the low-fidelity simulations. The results highlighted the robustness of the differentiable hybrid model in both training approaches. It delivered simulations that were at least 3.8 times faster than high-fidelity models. In the time-step-wise approach, it achieved at least a 39% improvement in accuracy. In the sequence-wise approach, it showed at least an 81% accuracy improvement over the full transient. This approach offers a promising path for improving computational efficiency without compromising accuracy in nuclear reactor simulations, making it suitable for real-time digital twin applications.

42 - ENGINEERING↗
DOE OSTI2025

A segmented approach to modeling building height: Delineating high-rise and low-rise buildings for enhanced height estimation

Understanding building height is imperative to the overall study of energy efficiency, population distribution, urban morphologies, emergency response, among others. Currently, existing approaches for modeling building height at scale are hindered by two pervasive issues. First, there is no consistent approach to quantify what a high-rise building is at a macro scale, leaving researchers unable to accurately compare results across geographies and domains. Second, high-rise buildings represent a small fraction of the built environment, implying data imbalance challenges that negatively affect current approaches. This is a problem of practical relevance since information on high-rise buildings is important for studies on urban heat islands, population dynamics, and pollution dispersion. Here, we introduce a novel approach to map building height which first identifies two distinct distributions within the built environment, with one being composed of low-rise buildings and one composed of high-rise buildings. We then develop an ensemble scheme where discrete specialist models are trained for each subset of low-rise buildings and high-rise buildings to infer building height from morphology features. For experiments mapping heights of 4.85 million buildings in Japan, we show an increase of 34 % in accuracy within 3m error when compared to the current state-of-the-art when modeling high-rise buildings, which based on KNN experimentation we define as any building > 12m . Our findings show that such an ensemble framework outperforms the current state-of-the-art approaches, which is especially relevant in relation to inferring height for high-rise buildings, a prominent issue of existing approaches for mapping the built environment.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Slender-body approach for computing second-order wave loads in the frequency domain

This work presents a slender-body approach to evaluate the second-order wave loads acting on a floating structure in the frequency domain. The approach is in the same spirit as the common use of Morison’s equation to approximate the wave loads without solving the radiation/diffraction problem. To do so, we employ Rainey’s equation, which can be seen as an extension of the inertial part of Morison’s equation to include nonlinear effects. We introduce modifications to Rainey’s formulation in order to evaluate wave kinematics at the mean body position instead of the original approach of considering instantaneous displacements. We also propose a simple approximation to partially account for wave scattering effects on the second-order loads based on the analytical solution of a surface-piercing bottom-mounted vertical circular cylinder. Though limited to structures composed of cylinders, this slender-body approach is orders of magnitude faster than computing second-order wave coefficients with a radiation/diffraction code. We implemented this approach for difference-frequency (slow drift) loads in an open-source frequency-domain floating wind turbine model. We present comparisons against results obtained with radiation/diffraction theory for three reference floating wind turbine designs: the OC3-Hywind spar, the OC4-DeepCwind semisubmersible, and the VolturnUS-S semisubmersible. In general, the results show that the proposed slender-body approach with the correction to approximate wave scattering effects provides useful estimations of the difference-frequency wave loads and the resulting motions of the floater.

17 WIND ENERGY↗
DOE OSTI2025

A Unified Framework to Reconcile Different Approaches of Modeling Transpiration Response to Water Stress: Plant Hydraulics, Supply Demand Balance, and Empirical Soil Water Stress Function

Plant responses to water stress is a major uncertainty to predicting terrestrial ecosystem sensitivity to drought. Different approaches have been developed to represent plant water stress. Empirical approaches (the empirical soil water stress (or Beta) function and the supply-demand balance scheme) have been widely used for many decades; more mechanistic based approaches, that is, plant hydraulic models (PHMs), were increasingly adopted in the past decade. However, the relationships between them—and their underlying connections to physical processes—are not sufficiently understood. This limited understanding hinders informed decisions on the necessary complexities needed for different applications, with empirical approaches being mechanistically insufficient, and PHMs often being too complex to constrain. Here we introduce a unified framework for modeling transpiration responses to water stress, within which we demonstrate that empirical approaches are special cases of the full PHM, when the plant hydraulic parameters satisfy certain conditions. We further evaluate their response differences and identify the associated physical processes. Finally, we propose a methodology for assessing the necessity of added complexities of the PHM under various climatic conditions and ecosystem types, with case studies in three typical ecosystems: a humid Midwestern cropland, a semi-arid evergreen needleleaf forest, and an arid grassland. Notably, Beta function overestimates transpiration when VPD is high due to its lack of constraints from hydraulic transport and is therefore insufficient in high VPD environments. With the unified framework, we envision researchers can better understand the mechanistic bases of and the relationships between different approaches and make more informed choices.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Efficient Neural Network Approaches for Conditional Optimal Transport with Applications in Bayesian Inference

In this work, we present two neural network approaches that approximate the solutions of static and dynamic conditional optimal transport (COT) problems. Both approaches enable conditional sampling and conditional density estimation, which are core tasks in Bayesian inference—particularly in the simulation-based (“likelihood-free”) setting. Our methods represent the target conditional distribution as a transformation of a tractable reference distribution. Obtaining such a transformation, chosen here to be an approximation of the COT map, is computationally challenging even in moderate dimensions. To improve scalability, our numerical algorithms use neural networks to parameterize candidate maps and further exploit the structure of the COT problem. Our static approach approximates the map as the gradient of a partially input convex neural network. It uses a novel numerical implementation to increase computational efficiency compared to state-of-the-art alternatives. Our dynamic approach approximates the conditional optimal transport via the flow map of a regularized neural ODE; compared to the static approach, it is slower to train but offers more modeling choices and can lead to faster sampling. We demonstrate both algorithms numerically, comparing them with competing state-of-the-art approaches, using benchmark datasets and simulation-based Bayesian inverse problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A Model-Based Systems Engineering Approach for Effective Decision Support of Modern Energy Systems Depicted with Clean Hydrogen Production

A holistic approach to decision-making in modern energy systems is vital due to their increase in complexity and interconnectedness. However, decision makers often rely on narrowly-focused strategies, such as economic assessments, for energy system strategy selection. The approach in this paper helps considers various factors such as economic viability, technological feasibility, environmental impact, and social acceptance. By integrating these diverse elements, decision makers can identify more economically feasible, sustainable, and resilient energy strategies. While existing focused approaches are valuable since they provide clear metrics of a potential solution (e.g., an economic measure of profitability), they do not offer the much needed system-as-a-whole understanding. This lack of understanding often leads to selecting suboptimal or unfeasible solutions, which is often discovered much later in the process when a change may not be possible. This paper presents a novel evaluation framework to support holistic decision-making in energy systems. The framework is based on a systems thinking approach, applied through systems engineering principles and model-based systems engineering tools, coupled with a multicriteria decision analysis approach. The systems engineering approach guides the development of feasible solutions for novel energy systems, and the multicriteria decision analysis is used for a systematic evaluation of available strategies and objective selection of the best solution. The proposed framework enables holistic, multidisciplinary, and objective evaluations of solutions and strategies for energy systems, clearly demonstrates the pros and cons of available options, and supports knowledge collection and retention to be used for a different scenario or context. The framework is demonstrated in case study evaluation solutions for a novel energy system of clean hydrogen generation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1973

Simulator evaluation of manually flown curved instrument approaches

Pilot performance in flying horizontally curved instrument approaches was analyzed by having nine test subjects fly curved approaches in a fixed-base simulator. Approaches were flown without an autopilot and without a flight director. Evaluations were based on deviation measurements made at a number of points along the curved approach path and on subject questionnaires. Results indicate that pilots can fly curved approaches, though less accurately than straight-in approaches; that a moderate wind does not effect curve flying performance; and that there is no performance difference between 60 deg. and 90 deg. turns. A tradeoff of curve path parameters and a paper analysis of wind compensation were also made.

Sager, D.↗
NASA NTRS1974

Simulator evaluation of manually flown curved MLS approaches

Pilot performance in flying horizontally curved instrument approaches was analyzed by having nine test subjects fly curved approaches in a fixed-base simulator. Approaches were flown without an autopilot and without a flight director. Evaluations were based on deviation measurements made at a number of points along the curved approach path and on subject questionnaires. Results indicate that pilots can fly curved approaches, though less accurately than streight-in approaches; that a moderate wind does not seriously affect curve flying performance; and that there is no major performance difference between 60 and 90 deg turns.

Sager, D.↗
NASA NTRS1975

Modification to area navigation equipment for instrument two-segment approaches

A two-segment aircraft landing approach concept utilizing an area random navigation (RNAV) system to execute the two-segment approach and eliminate the requirements for co-located distance measuring equipment (DME) was investigated. This concept permits non-precision approaches to be made to runways not equipped with ILS systems, down to appropriate minima. A hardware and software retrofit kit for the concept was designed, built, and tested on a DC-8-61 aircraft for flight evaluation. A two-segment approach profile and piloting procedure for that aircraft that will provide adequate safety margin under adverse weather, in the presence of system failures, and with the occurrence of an abused approach, was also developed. The two-segment approach procedure and equipment was demonstrated to line pilots under conditions which are representative of those encountered in air carrier service.

Source record↗
NASA NTRS1976

Flight evaluation of two-segment approaches using area navigation guidance equipment

A two-segment noise abatement approach procedure for use on DC-8-61 aircraft in air carrier service was developed and evaluated. The approach profile and procedures were developed in a flight simulator. Full guidance is provided throughout the approach by a Collins Radio Company three-dimensional area navigation (RNAV) system which was modified to provide the two-segment approach capabilities. Modifications to the basic RNAV software included safety protection logic considered necessary for an operationally acceptable two-segment system. With an aircraft out of revenue service, the system was refined and extensively flight tested, and the profile and procedures were evaluated by representatives of the airlines, airframe manufacturers, the Air Line Pilots Association, and the Federal Aviation Adminstration. The system was determined to be safe and operationally acceptable. It was then placed into scheduled airline service for an evaluation during which 180 approaches were flown by 48 airline pilots. The approach was determined to be compatible with the airline operational environment, although operation of the RNAV system in the existing terminal area air traffic control environment was difficult.

Schwind, G. K.↗
NASA NTRS1976

Noise measurements for a twin-engine commercial jet aircraft during 3 deg approaches and level flyovers

Noise measurements have been made with a twin-engine commercial jet aircraft making 3 deg approaches and level flyovers. The flight-test data showed that, in the standard 3 deg approach configuration with 40 deg flaps, effective perceived noise level (EPNL) had a value of 109.5 effective perceived noise decibels (EPNdB). This result was in agreement with unpublished data obtained with the same type of aircraft during noise certification tests; the 3 deg approaches made with 30 deg flaps and slightly reduced thrust reduced the EPNL value by 1 EPNdB. Extended center-line noise determined during the 3 deg approaches with 40 deg flaps showed that the maximum reference A-weighted sound pressure level (LA,max)ref varied from 100.0 A-weighted decibels 2.01 km (108 n. mi.) from the threshold to 87.4 db(A) at 6.12 km (3.30 n. mi.) from the threshold. These test values were about 3 db(A) higher than estimates used for comparison. The test data along the extended center line during approaches with 30 deg flaps were 1 db(A) lower than those for approaches with 40 deg flaps. Flight-test data correlating (LA,max)ref with thrust at altitudes of 122 m (400 ft) and 610 m (2000 ft) were in agreement with reference data used for comparison.

Hastings, E. C., Jr.↗
NASA NTRS1977

Test particle propagation in magnetostatic turbulence. 3: The approach to equilibrium

The asymptotic behavior, for large time, of the quasi-linear diabatic solutions and their local approximations is considered. A time averaging procedure is introduced which yields the averages of these solutions over time intervals which contain only large time values. A discussion of the quasi-linear diabatic solutions which is limited to those solutions that are bounded from below as functions of time is given. It is shown that as the upper limit of the time averaging interval is allowed to approach infinity the time averaged quasi-linear diabatic solutions must approach isotropy (mu-independence). The first derivative with respect to mu of these solutions is also considered. This discussion is limited to first derivatives which are bounded functions of time. It is shown that as the upper limit of the time averaging interval is allowed to approach infinity, the time averaged first derivative must approach zero everywhere in mu except at mu = 0 where it must approach a large value which is calculated. The impact of this large derivative on the quasi-linear expansion scheme is discussed. An H-theorem for the first local approximation to the quasi-linear diabatic solutions is constructed. Without time averaging, the H-theorem is used to determine sufficient conditions for the first local approximate solutions to asymptote, with increasing time, to exactly the same final state which the time averaged quasi-linear diabatic solutions must approach as discussed above.

Klimas, A. J.↗
NASA NTRS1976

Effect of multiple path approach procedures on runway landing capacity

When using the Instrument Landing System (ILS) all aircraft must follow a straight line approach path before landing. The Microwave Landing System (MLS) will allow use of differing curved approach paths. The objective of this research is to find out whether the introduction of MLS and consequently multiple approach paths can bring an increase in runway landing capacity. A model is developed which is capable of computing the expected ultimate landing runway capacity, under ILS and MLS conditions, when aircraft population characteristics and Air Traffic Control separation rules are given. This model can be applied in situations when only a horizontal separation between aircraft approaching a runway is allowed, as well as when both vertical and horizontal separations are possible. Results suggest that an increase in runway landing capacity, caused by introducing the MLS-described multiple approach paths, is to be expected only when an aircraft population consists of aircraft with significantly differing approach velocities and particularly in situations when a vertical separation can be applied.

Tosic, V.↗
NASA NTRS1978

Airline pilot scanning behavior during approaches and landing in a Boeing 737 simulator

A series of approaches using airline-rated Boeing 737 pilots in an FAA qualified simulator was conducted. The test matrices include both manual and coupled approaches for VFR, Category 1 and Category 2 conditions. A nonintrusive oculometer system was used to track the pilot's eye-point-of-regard throughout the approach. The results indicate that, in general, the pilots use a different scan technique for the manual and coupled (auto-pilot with manual throttle) conditions. For the manual approach 73 percent of the time was spent on the Flight Director and 13 percent on airspeed as opposed to 50 percent on Flight Director and 23 percent on airspeed for the coupled approaches. For the visual portion of approach from less than 100m to touchdown or when the touchdown point came into view, the pilots tend to fixate on their aim or touchdown area until the flare initiation, at which time they let their eye-point-of-regard move up the runway to use the centerline lights for rollout guidance.

Spady, A. A., Jr.↗
NASA NTRS1977

Airline pilot scanning behavior during approaches and landing in a Boeing 737 simulator

A series of approaches using airline-rated Boeing 737 pilots in an FAA qualified simulator has been conducted. The test matrices include both manual and coupled approaches for VFR, Category I and Category II conditions. A nonintrusive oculometer system was used to track the pilot's eye-point-of-regard throughout the approach. The results indicate that, in general, the pilots use a different scan technique for the manual and coupled (auto-pilot with manual throttle) conditions. For the manual approach 73 percent of the time was spent on the Flight Director and 13 percent on airspeed as opposed to 50 percent on Flight Director and 23 percent on airspeed for the coupled approaches. For the visual portion of approach from less than 100 m (300 ft) to touchdown or when the touchdown point came into view, the pilots tend to fixate on their aim or touchdown area until the flare initiation, at which time they let their eye-point-of-regard move up the runway to use the centerline lights for rollout guidance.

Spady, A. A., Jr.↗