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43 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

An iterative bidirectional gradient boosting approach for CVR baseline estimation

Here this paper presents a novel Iterative Bidirectional Gradient Boosting Model (IBi-GBM) for estimating the baseline of Conservation Voltage Reduction (CVR) programs. In contrast to many existing methods, we treat CVR baseline estimation as a missing data retrieval problem. The approach involves dividing the load and its corresponding temperature profiles into three periods: pre-CVR, CVR, and post-CVR. To restore the missing load profile during the CVR period, the method employs a three-step process. First, a forward-pass GBM is executed using data from the pre-CVR period as inputs. Subsequently, a backward-pass GBM is applied using data from the post-CVR period. The two restored load profiles are reconciled, considering pre-calculated weights derived from forecasting accuracy, and only the leftmost and rightmost points are retained. The newly restored points are then included as inputs for the subsequent iteration. This iterative procedure continues until the original load data in the CVR period is fully restored. We develop IBi-GBM using actual smart meter and Supervisory Control and Data Acquisition (SCADA) data. Our results demonstrate that IBi-GBM exhibits robust performance across various data resolutions and in different seasons and outperforms existing methods by achieving a 1-2% reduction in normalized Root Mean Square Error (nRMSE).

42 ENGINEERING↗
NASA NTRS2018

Methodologies for Verification and Validation of Space Launch System (SLS) Structural Dynamic Models

Responses to challenges associated with verification and validation (V&V) of Space Launch System (SLS) structural dynamics models are presented in this paper. Four methodologies addressing specific requirements for V&V are discussed. (1) Residual Mode Augmentation (RMA), which has gained acceptance by various principals in the NASA community, defines efficient and accurate FEM modal sensitivity models that are useful in test-analysis correlation and reconciliation and parametric uncertainty studies. (2) Modified Guyan Reduction (MGR) and Harmonic Reduction (HR, introduced in 1976), developed to remedy difficulties encountered with the widely used Classical Guyan Reduction (CGR) method, are presented. MGR and HR are particularly relevant for estimation of "body dominant" target modes of shell-type SLS assemblies that have numerous "body", "breathing" and local component constituents. Realities associated with configuration features and "imperfections" cause "body" and "breathing" mode characteristics to mix resulting in a lack of clarity in the understanding and correlation of FEM- and test-derived modal data. (3) Mode Consolidation (MC) is a newly introduced procedure designed to effectively "de-feature" FEM and experimental modes of detailed structural shell assemblies for unambiguous estimation of "body" dominant target modes. Finally, (4) Experimental Mode Verification (EMV) is a procedure that addresses ambiguities associated with experimental modal analysis of complex structural systems. Specifically, EMV directly separates well-defined modal data from spurious and poorly excited modal data employing newly introduced graphical and coherence metrics.

Coppolino, Robert N.↗
NASA NTRS2011

Impact of Vehicle Flexibility on IRVE-II Flight Dynamics

The Inflatable Re-entry Vehicle Experiment II (IRVE-II) successfully launched from Wallops Flight Facility (WFF) on August 17, 2009. The primary objectives of this flight test were to demonstrate inflation and re-entry survivability, assess the thermal and drag performance of the reentry vehicle, and to collect flight data for refining pre-flight design and analysis tools. Post-flight analysis including trajectory reconstruction outlined in O Keefe3 demonstrated that the IRVE-II Research Vehicle (RV) met mission objectives but also identified a few anomalies of interest to flight dynamics engineers. Most notable of these anomalies was high normal acceleration during the re-entry pressure pulse. Deflection of the inflatable aeroshell during the pressure pulse was evident in flight video and identified as the likely cause of the anomaly. This paper provides a summary of further post-flight analysis with particular attention to the impact of aeroshell flexibility on flight dynamics and the reconciliation of flight performance with pre-flight models. Independent methods for estimating the magnitude of the deflection of the aeroshell experienced on IRVE-II are discussed. The use of the results to refine models for pre-flight prediction of vehicle performance is then described.

Bose, David M.↗
NASA NTRSDate not supplied

A Method for Validating Causal Diagrams of Human Health Risk in Space Flight

The complexity of cause-and-effect relationships between spaceflight hazards and resulting health conditions clouds understanding of the totality of human system risk in space. In response, NASA has introduced Directed Acyclic Graphs (causal diagrams) into the human systems risk management process. These diagrams allow for a common understanding of the mechanisms that lead from unique hazards of spaceflight to the health outcomes important to agencies and astronauts. However, the paucity of available biomedical data from spaceflight creates a need for methods of validating causal models that can accommodate data from spaceflight model analogs. Here we outline one approach utilizing open-access rodent bone datasets from the Ames Life Sciences Data Archive. The properties of directed acyclic graphs themselves can provide an epistemological and statistical framework for validation of a priori causal representations of human system risk in space flight. The assumed causal connections on the graph creates sets of logical implications: variables that – if the causal diagram is correct – should be correlated, as well as sets that should be conditionally independent. By testing these implied correlations and conditional independencies both statistically and heuristically, we can provide evidence for or against specific causal pathways on the causal diagram. In addition to validation of expert-generated causal diagrams, machine learning techniques can learn the most likely structure of a causal diagram from a given dataset. Comparison with and reconciliation between machine-learned causal diagrams and expert-generated diagrams is another technique for challenging assumptions and improving our understanding of causal mechanisms. Accurately representing complex causation is essential to systemic understanding of human health risks in space travel. Having a robust system of validating causal diagrams helps us arrive at more accurate representations of causal systems. This process will be integral to developing the countermeasures necessary for extended exploration of the moon and Mars.

Robert Reynolds↗
NASA NTRS1932

Statistics of the Bureau Veritas

Statistics are indispensable factors for the amelioration of safety. Through the reconciliation of accidents which may appear isolated to interested parties, they permit tracking of typical causes of accidents; conversely, they can prevent, after a serious accident due to some fortuitous cause, the taking of incautious measures under the pressure of public opinion, which always inclines to gauge the gravity of the causes by that of the results. Lastly, they permit appraisal of the efficacy of rules in force. We should add that statistics provide an agency of prevention for future accidents. A careful inspection of all signs of malfunction of material quite often prevents the occurrence of an accident. In this respect, many pilot's report, perfectly normal in every way as far as operation is concerned, can reveal much more interesting technical data than an accident, although it does not diminish the importance of statistics. Therefore, from the inception of its aeronautical service, at the end of 1922, the Bureau Veritas has kept annual statistics of all accidents which occurred in French civil aviation. In order to correctly perform their proper function, the statistics must be exact and sufficiently explicit and complete. To be exact, they must bear on all pertinent events, and on these alone. It is a matter then, first of all, defining the accident in such a way that no sinister detail bearing on the definition may escape control. The consideration of accidents to personnel only has appeared too limited. One of the essential qualities of statistics is to permit the taking of averages and in consequence to apply them ot a sufficiently large number; such is happily not the case in accidents to personnel.

Volmerange, Andre↗
DOE OSTI2025

Progress in modeling hydrogen assisted ammonia oxidation with new experiments and a further reconciliation of the NH 3 + OH rate constant

Hydrogen-assisted oxidation of ammonia in a premixed, laminar flow tubular reactor under reducing conditions was investigated experimentally and through chemical kinetic modeling. Due to its impact on the competition for OH among ammonia and hydrogen, the rate constant for NH 3 + OH (R1) was determined through state-of-the-art theoretical kinetics calculations, employing composite energies that include the effects of higher order electronic excitations on the electronic energies along the variational reaction path and treating the limitations in the kinetics posed by the passage through a hydrogen-bonded complex. The resulting rate constant was in close agreement with the recent experimental value from Zaczek et al. (2025), settling a long-term dispute about the high-temperature value of k 1 and confirming within 20% the value previously used in modeling. The chemical kinetic model, with no other changes, captured well measured concentrations of NH 3 , H 2 , NO, and N 2 O from flow reactor oxidation of NH 3 /H 2 at slightly reducing conditions over a range of temperature (900-1350 K) and NH 3 /H 2 ratios (0.5-2.0). Comparison of the present results with reported data from a non-premixed setup indicates that for laminar flow tubular reactors, the reactor configuration may have implications for the observed H 2 consumption due to the possibility of preferential oxidation during mixing.

Ab initio theory↗
DOE OSTI2022

An independent analysis of bias sources and variability in wind plant pre-construction energy yield estimation methods

The wind resource assessment community has long had the goal of reducing the bias between wind plant pre-construction energy yield assessment (EYA) and the observed annual energy production (AEP). This comparison is typically made between the 50% probability of exceedance (P50) value of the EYA and the long-term corrected operational AEP (hereafter OA P50), and is known as the P50 bias. The industry has critically lacked an independent analysis of bias reduction investigated across multiple consultants to identify the greatest sources of uncertainty and variance in the EYA process and the best opportunities for uncertainty reduction. The present study addresses this gap by benchmarking consultant methodologies against each other and against operational data at a scale not seen before in industry collaborations. We consider data from 10 wind plants and evaluate discrepancies between eight consultancies in the steps taken from estimates of gross to net energy. Consultants tend to overestimate the gross energy produced at the turbines and then compensate by further overestimating downstream losses, leading to a mean P50 bias near zero, still with significant variability among the individual wind plants. Within our data sample, we find that consultant estimates of all loss categories, except environmental losses, tend to reduce the project-to-project variability of the P50 bias. The disagreement between consultants, however, remains flat throughout the addition of losses. Finally, we find that differences in consultants’ estimates of project performance can lead to differences up to $10/MWh in the levelized cost of energy for a wind plant.

Todd, Austin C.↗