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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.

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At least 343 records · Page 19

High-Efficiency Flexible Multilevel Photon Sieves by Single-Step Laser-Based Fabrication and Optical Analysis

Over the past several decades, the need for high-resolution, high-efficiency, lightweight, high contrast focusing optics has continued to increase due to their applications in fields such as astronomy, spectroscopy, free-space optical communications, defense, and remote sensing. In recent years, photon sieve planar diffractive optics have been developed on flexible, lightweight polyimide substrates. However, transmission efficiencies have continuously been very low (~1-4%), thus impeding the widespread use of photon sieves in practical applications. Here, we present a flexible, lightweight, N = 4 level phase photon sieve with over 25% transmission efficiency; nearly triple that of any other photon sieve reported thus far. In this study, the photon sieve was fabricated via a novel pulsed laser ablation method using an ultraviolet source, and the total time to fabricate a ~3 sq cm sample was tens of seconds. Theoretical analysis of the photon sieve was carried out via the FDTD method, and was in very good agreement with experimental results. We also calculated via FDTD modeling the behavior of higher step (N = 8, 16, 32) photon sieves for further enhanced efficiencies, and show a fundamental limit on photon sieve efficiency of 70% in the limit of increasing step number. This multilevel photon sieve represents a new step in high-resolution diffractive optics, moving towards efficiencies suitable for widespread applications.

Julian, Matthew N.↗

High-Frequency Secondary Instabilities Downstream of a Forward-Facing Step

Localized high-frequency velocity fluctuations were measured downstream of a forward-facing step on a 30◦swept flat plate with an imposed pressure gradient. Phase-locked time-resolved particle image velocimetry measurements were performed to determine the source of the fluctuations, which ultimately lead to transition. The steps result in localized regions of reversed flow for a short region downstream of the step. These regions are highly localized due to the impact of the stationary crossflow vortices. The velocity fluctuations typically increase significantly in amplitude shortly downstream of reattachment in these localized regions, indicating that the fluctuations are related to reattachment of the shear layer. The phase-averaged measurements confirm that the unsteadiness in the shear layer results in the shedding of a plethora of vortices, some oriented in the streamwise direction, and others in the spanwise direction. These vortices are impacted by the local properties of the mean flow, such as streamwise vorticity and streamwise velocity gradient. The origin of the unsteadiness in the shear layer is not definitively shown, but evidence suggests it is due to a shear-layer instability. Ultimately, the unsteadiness of the shear layer, and the vortices that are shed as a result of this unsteadiness, are responsible for transition in this scenario.

Jenna L Eppink↗

One Step Plasma Passivation and Precision Cleaning

Over the past several years, Kennedy Space Center (KSC) researchers developed two solvent-free techniques for precision cleaning of ground support equipment (GSE) that possess low commodity requirements and produce small or no waste streams. During testing of low-pressure air plasma as one of these cleaning techniques, physical changes in the surface of stainless steel test pieces were observed; cursory testing revealed that the test part had developed a thick oxide layer on the surface compared to untreated parts. This result indicated that the plasma process might not only serve as a green technology for precision cleaning of parts, but it may also passivate the surface at the same time. Current methodology in use at KSC’s Components Refurbishment & Chemical Analysis (CRCA) Facility for passivation of corrosion-resistant steels for aerospace applications follows an SAE International Standard, AMS2700, where parts are submerged in either a nitric acid or nitric acid/sodium dichromate bath at predetermined temperatures and contact times. These baths require constant testing to ensure effective treatment, use corrosive and carcinogenic chemicals, and produce hazardous waste. The passivation bath is one of the multiple steps employed at the facility, while cleaning with multiple environmentally-unfriendly solvents comprise several more steps before parts are recertified to a specific cleanliness level in their clean room. Based on the behavior of the stainless steel surface during cleaning optimization studies, it was believed that the plasma technology could be extended to passivation, combining what is currently many steps into a single, solvent- and waste-free system.

Paul Hintze↗

A Recursive Multi-step Machine Learning Approach for Airport Configuration Prediction

Airport configuration selection is a complex decision-making process that involves several operational and human factors. In this paper we propose a novel recursive multi-step machine learning (ML) approach to predict airport configuration. The multi-step approach guarantees stability of the predicted configuration by taking as input the configuration predicted at the previous time step. The features of the proposed model include weather data, future arrival and departure counts and current configuration. Due to the importance of arrival and departure counts in predicting the airport configuration, arrival counts are calculated using landing time predictions selected from physics-based landing time predictions available in FAA System Wide Information Management data feeds for each flight. The selection rules were developed and refined to select the most accurate time for different phases of flight. The proposed model predicts the airport configurations up to 6 hours ahead. In this paper we show the predictive performance of the proposed model for six major US airports, including Charlotte Douglas International Airport (CLT), Dallas/Fort Worth International Airport (DFW), John F. Kennedy International Airport (JFK), Newark Liberty International Airport (EWR), LaGuardia Airport (LGA) and Dallas Love Field Airport (DAL). We trained and evaluated models on 2019 and 2020 data in order to study the effect of the pandemic and how changes in traffic patterns affected the performance of the proposed model. Results are compared with a baseline assuming no airport configuration changes. In our results for DFW, we obtained a prediction accuracy of 89.3% for 3 hours ahead prediction, and 82.8% for 6 hours ahead when applied on 2019 data.

machine learning↗

A Recursive Multi-step Machine Learning Approach for Airport Configuration Prediction

Airport configuration selection is a complex decision-making process that involves several operational and human factors. In this paper we propose a novel recursive multi-step machine learning (ML) approach to predict airport configuration. The multi-step approach guarantees stability of the predicted configuration by taking as input the configuration predicted at the previous time step. The features of the proposed model include weather data, future arrival and departure counts and current configuration. Due to the importance of arrival and departure counts in predicting the airport configuration, arrival counts are calculated using landing time predictions selected from physics-based landing time predictions available in FAA System Wide Information Management data feeds for each flight. The selection rules were developed and refined to select the most accurate time for different phases of flight. The proposed model predicts the airport configurations up to 6 hours ahead. In this paper we show the predictive performance of the proposed model for six major US airports, including Charlotte Douglas International Airport (CLT), Dallas/Fort Worth International Airport (DFW), John F. Kennedy International Airport (JFK), Newark Liberty International Airport (EWR), LaGuardia Airport (LGA) and Dallas Love Field Airport (DAL). We trained and evaluated models on 2019 and 2020 data in order to study the effect of the pandemic and how changes in traffic patterns affected the performance of the proposed model. Results are compared with a baseline assuming no airport configuration changes. In our results for DFW, we obtained a prediction accuracy of 89.3% for 3 hours ahead prediction, and 82.8% for 6 hours ahead when applied on 2019 data.

machine learning↗

Automated Technique for the Detection of Step-Like Solar Wind Dynamic Pressure Changes: Application to the Response of the Transpolar Potential to Solar Wind Dynamic Pressure Fronts

The input from the solar wind (SW) and the accompanying Interplanetary Magnetic Field (IMF) is the defining feature of the solar wind-magnetosphere interactions. One of the most important SW drivers is the solar wind dynamic pressure, and most significantly its sharp changes known as pressure fronts. Sudden enhancements in solar wind dynamic pressure, SWP, have been shown to lead to intensification of the auroral electrojets (and Region 1 field-aligned currents), increase in auroral emissions, and significant enhancement in ionospheric convection and the transpolar potential. Case studies of the interaction between pressure fronts and the terrestrial space environment shed great light on their importance to the structure and dynamics of the system. However, thorough understanding of the interaction requires fully statistical investigations. These statistical studies require a large number of suitable pressure front events. In the past these have been obtained through laborious manual inspection of solar wind data. We present an automated procedure that identifies sudden step enhancements in SWP that satisfy a desired set of limiting step-like characteristics, such as magnitude of the change, sign of the change (positive/negative), and rate of change. The procedure yields a list of suitable events, along with their step features within minutes. The technique is tested for missed events and false positives by direct comparison to manual inspection of the data. Its utility is illustrated by application to the statistical effect of pressure fronts to the transpolar potential as measured by the Assimilative Mapping of Ionospheric Electrodynamics (AMIE) technique.

A. Boudouridis↗

A Large-Eddy Simulation Of Turbulent Flow Over A Backward Facing Step

Large-eddy simulation (LES) was used to study the turbulent flow over a backward facing step. The simulations examine the details of the turbulent flow’s separated and reattaching regions created by the step geometry. An explicit high-order of accuracy/high resolution finite-difference computational fluid dynamics solver was used for both LES and Reynolds-averaged Navier-Stokes (RANS) simulations. The experimental data from the backward facing step experiment of Driver and Seegmiller was used for comparison. Data presented are derived from a RANS simulation using the Spalart-Allmaras turbulence model and LES simulations using the implicit LES assumption on three different grids of varying resolution. The RANS solution agrees with past work. It does an adequate job of predicting the flowfield and reattachment point, but misses details such as the strength of the recirculating region and magnitudes of the Reynolds stresses. The synthetic eddy method was used to provide a turbulent inflow to the quasi-2D LES domains. For the LES, the coarse grid was of insufficient resolution and under-predicted the skin friction coefficient and over-predicted the normal stresses. The finer grid LES results accurately predict the skin friction coefficient and provide more accurate Reynolds stresses. Triple product velocity correlations are also computed from the LES and the finer grid results did a good job predicting the magnitudes of the curves and the shapes were reasonably represented. It is recommended that future work include investigating the turbulent inflow domain length, width of the quasi-2D domain, and additional grid refinement

turbulence↗

A Large-Eddy Simulation Of Turbulent Flow Over A Backward Facing Step

Large-eddy simulation (LES) was used to study the turbulent flow over a backward facing step. The simulations examine the details of the turbulent flow's separated and reattaching regions created by the step geometry. An explicit high-order of accuracy/high resolution finite-difference computational fluid dynamics solver was used for both LES and Reynolds-averaged Navier-Stokes (RANS) simulations. The experimental data from the backward facing step experiment of Driver and Seegmiller was used for comparison. Data presented are derived from a RANS simulation using the Spalart-Allmaras turbulence model and LES simulations using the implict LES assumption on three different grids of varying resolution. The RANS solution agrees with past work. It does an adequate job of predicting the flowfield and reattachment point, but misses details such as the strength of the recirculating region and magnitudes of the Reynolds stresses. The synthetic eddy method was used to provide a turbulent inflow to the quasi-2D LES domains. For the LES, the coarse grid was of insufficient resolution and under-predicted the skin friction coefficient and over-predicted the normal stresses. The finer grid LES results accurately predict the skin friction coefficient and provide more accurate Reynolds stresses. Triple product velocity correlations are also computed from the LES and the finer grid results did a good job predicting the magnitudes of the curves and the shapes were reasonably represented. It is recommended that future work include investigating the turbulent inflow domain length, width of the quasi-2D domain, and additional grid refinement.

turbulence↗

Obtaining Accurate Derivatives Across Adaptive-Step Integration

Obtaining derivatives through the integration of a set of ordinary differential equations is of interest to a number of fields of research. Approaches for doing so that are available in the literature, however, do not account for details associated with variable step integrator that cause inaccuracies in the total derivatives. In this paper, we explore the causes of the accumulation of derivative error in adaptive-step Runge-Kutta integration schemes and propose a solution to eliminate them. The new algorithm proposed is a transformation of each step of a Runge-Kutta integration into a set of residual equations. This work demonstrates the improvement in accuracy of total derivatives when the new algorithm is utilized.

Kaushik Ponnapalli↗

Hydraulic Response to Thermal Stimulation Efforts at Raft River Based on Stepped Rate Injection Testing

The injection well stimulation project at the Raft River geothermal field tests the effect of long-term cold water injection and high pressure injection on well injectivity, improvements to which could reduce operating costs. The primary data for analysis and interpretation of the injection test are step-rate flow tests run before each new phase of the injection. These tests were analyzed using a combination of standard pump-test analytical solution methods and methods developed expressly for the observed conditions. The stepped rate injection tests, combined with long-term flow and pressure response data suggest that the well is located within a fractured formation of low transmissivity but high storativity. These calculated parameters appeared to increase with pressure during the first injection test and the higher values were reproduced during the second stepped rate test. Calculated transmissivity and storativity are on the order of 4E-5 m cm 2 and 1E-4 m Pa -1 , respectively. The apparent pressure dependence of fitted hydraulic parameters may reflect near-well fracture compliance that increased the effective radius of the wellbore during the first test. While the type curve fit analysis also suggests that the reservoir behaves as a uniformly fractured reservoir with a radial flow regime, the hydraulic parameters indicate that condition may exist only a very limited distance (<10 m) from the well. Longer-term pressure response suggests that flow in the system effectively reaches steady state in a period of less than a day, which may reflect pressure stabilization resulting from pressure-dependent permeability or a region of much higher permeability located with a few meters of the well. The transmissivity estimates obtained from this analysis, converted to approximate fracture density and aperture, provide useful constraints on the distance to which the thermal front may migrate from the well during the cold water injection phase of the stimulation project. We estimate that the cooling front will migrate less than a tenth of a kilometer over an approximately one-year injection period. Here, the effects of that cooling, however, may be substantial, because increases in permeability have maximum effect nearest the well.

cold water injection↗

14 Steps to Creating Value in Cost and Schedule Resources for Nuclear Waste Management - 20188

While Waste Management budgets are shrinking, DOE required cost and schedule controls are becoming increasingly stringent. At the same time, there is a scarcity of adept, qualified, and competent projects controls staff who both understand nuclear waste management and are capable of addressing today's cost and schedule challenges. In response, we have developed a systematic approach to training and mentoring project controls staff. The approach is based on the observations and lessons learned on projects, both successful and unsuccessful, over the past 20 years. During that time, we evaluated staff development and used that experience to design a program that progresses the maturity, knowledge and experience of the individual. The program is based on the unique needs of cost and schedule specialists while incorporating the best leadership and managerial applications. The system is not limited to developing individual software skills, which is a primary focus of many project controls training programs. Instead, our system develops an individual's soft and hard skill sets. The system develops the user's skill, talent, attitude, and drive to do the best job possible. It focuses on all aspects of becoming a more productive technical team while accepting responsibility for individual growth. It also enhances the project controls team by setting up checks and balances that everyone is aware of and participates in. The system is based on 14 steps of increasing complexity in knowledge and application. The system clarifies roles, responsibilities and expectations. It helps eliminate uncertainty and reduces stress on staff and managers. It contains everyday routine actions and is simple to implement. It allows the development of a consistent rhythm to staff growth and development. Mastering the steps will allow the user to achieve excellence in cost and schedule control. The 14 steps are: 1 - Key Performance Objectives, 2 - Check Lists, 3 - Desktop Guides, 4 - System Description, 5 - Procedures, 6 - Software and On the Job Training (OTJ), 7 - Traceability Checks, 8 - Surveillances, 9 - 32 Criteria, 10 - The Contract, 11 - Customer/Government Guidance, 12 - Training and Mentoring Others, 13 - Master your weekly and daily schedules, 14 - Improving your interpersonal skills. Application and mastery of this system will produce better cost and schedule control results. Your project controls staff will write better reports, analyze data better, make better use of their time, and be more valuable to decision makers. If followed rigorously, our system will produce a great project controls team, which is invaluable to the success of each project. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Multi–Step Nucleation of a Crystalline Silicate Framework via a Structurally Precise Prenucleation Cluster

Hierarchical nucleation pathways are ubiquitous in the synthesis of minerals and materials. In the case of zeolites and metal–organic frameworks, pre-organized multi-ion “secondary building units” (SBUs) have been proposed as fundamental building blocks. However, detailing the progress of multi-step reaction mechanisms from monomeric species to stable crystals and defining the structures of the SBUs remains an unmet challenge. Furthermore, combining in situ nuclear magnetic resonance, small-angle X-ray scattering, and atomic force microscopy, we show that crystallization of the framework silicate, cyclosilicate hydrate, occurs through an assembly of cubic octameric Q 3 8 polyanions formed through cross-linking and polymerization of smaller silicate monomers and other oligomers. These Q 3 8 are stabilized by hydrogen bonds with surrounding H 2 O and tetramethylammonium ions (TMA + ). When Q 3 8 levels reach a threshold of ≈32 % of the total silicate species, nucleation occurs. Further growth proceeds through the incorporation of [(TMA) x (Q 3 8 )•n H 2 O] (x–8) clathrate complexes into step edges on the crystals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Explainable machine learning model for multi-step forecasting of reservoir inflow with uncertainty quantification

We propose an explainable machine learning (ML) model with uncertainty quantification (UQ) to improve multi-step reservoir inflow forecasting. Traditional ML methods have challenges in forecasting inflows multiple days ahead, and lack explainability and UQ. To address these limitations, we introduce an encoder–decoder long short-term memory (ED-LSTM) network for multi-step forecasting, employ the SHapley Additive exPlanation (SHAP) technique for understanding the influence of hydrometeorological factors on inflow prediction, and develop a novel UQ method for prediction trustworthiness. We apply these methods to forecast 7-day inflow in snow-dominant and rain-driven reservoirs. The results demonstrate the effectiveness of the ED-LSTM model, with high forecasting accuracy for short lead times. Our UQ method provides reliable uncertainty estimates, covering 90% of data with a 90% confidence level. The SHAP analysis reveals the importance of historical inflow and precipitation as influential factors. These findings and methods may support reservoir operators in optimizing water resources management decisions.

54 ENVIRONMENTAL SCIENCES↗

Optimal checkpointing for adjoint multistage time-stepping schemes

Here, we consider checkpointing strategies that minimize the number of recomputations needed when performing discrete adjoint computations using multistage time-stepping schemes that require computing several substeps within one complete time step. Specifically, we propose two algorithms that can generate optimal checkpoint-ing schedules under weak assumptions. The first is an extension of the seminal Revolve algorithm adapted to multistage schemes. The second algorithm, named CAMS, is developed based on dynamic programming, and it requires the least number of recomputations when compared with other algorithms. The CAMS algorithm is made publicly available in a library with bindings to C and Python. Numerical results show that the proposed algorithms can deliver up to two times the speedup compared with that of classical Revolve. Moreover, we discuss the utilization of the CAMS library in mature scientific computing libraries and demonstrate the ease of using it in an adjoint workflow. The proposed algorithms have been adopted by the PETSc TSAdjoint library. Their performance has been demonstrated with a large-scale PDE-constrained optimization problem on a leadership-class supercomputer. This work is a significant extension of the authors' conference paper.

97 MATHEMATICS AND COMPUTING↗

Precursory Off-Fault Deformation in Restraining and Releasing Step Overs: Insights From Discrete Element Method Models

Accelerating geophysical activity is detected preceding some, but not all, large earthquakes. This observation may indicate that no precursors occur before some earthquakes, or that the instrumentation lacks the required sensitivity. Here, to aid crustal monitoring efforts, we use discrete element method models to identify the locations and styles of deformation that may provide useful information about approaching fault reactivation. We model the reactivation of two healed rough faults in a variety of step over configurations, embedded in a host rock with varying amounts of damage subject to shear velocity loading parallel to the faults. Both the fault geometry and ratio of fault to host rock strength control the amount of off-fault deformation. Consistent with field observations, models with larger steps and more preexisting host rock damage produce higher amounts of off-fault deformation. We assess the size of the continuous regions of high velocities and strains to compare the value of the precursory information of each velocity and strain component. Comparing the three components of the velocity vector suggests that the fault-parallel velocity produces the largest and most temporally continuous regions of elevated velocity. The size of these regions increases toward failure, indicating the usefulness of tracking this component. Comparing the volumetric and shear components of the three-dimensional strain tensor suggests that during most of the interseismic period, the shear strain provides more information about approaching fault slip than the volumetric strain. However, in the days and months preceding fault reactivation, both the shear and volumetric strains provide similarly valuable information.

58 GEOSCIENCES↗

Effects of a CFD-improved dimple stepped-lip piston on thermal efficiency and emissions in a medium-duty diesel engine

Diesel piston-bowl shape is a key design parameter that affects spray-wall interactions and turbulent flow development, and in turn affects the engine’s thermal efficiency and emissions. It is hypothesized that thermal efficiency can be improved by enhancing squish-region vortices as they are hypothesized to promote fuel-air mixing, leading to faster heat-release rates. However, the strength and longevity of these vortices decrease with advanced injection timings for typical stepped-lip (SL) piston geometries. Dimple stepped-lip (DSL) pistons enhance vortex formation at early injection timings. Previous engine experiments with such a bowl show 1.4% thermal efficiency gains over an SL piston. However, soot was increased dramatically [SAE 2022-01-0400]. In a previous study, a new DSL bowl was designed using non-combusting computational fluid dynamic simulations. This improved DSL bowl is predicted to promote stronger, more rotationally energetic vortices than the baseline DSL piston: it employs shallower, narrower, and steeper-curved dimples that are placed further out into the squish region. In the current experimental study, this improved bowl is tested in a medium-duty diesel engine and compared against the SL piston over an injection timing sweep at low-load and part-load operating conditions. No substantial thermal efficiency gains are achieved at the early injection timing with the improved DSL design, but soot emissions are lowered by 45% relative to the production SL piston, likely due to improved air utilization and soot oxidation. However, these benefits are lost at late injection timings, where the DSL piston renders a lower thermal efficiency than that of the SL piston. Energy balance analyses show higher wall heat transfer with the DSL piston than with the SL piston despite a 1.3% reduction in the piston surface area. Vortex enhancement may not necessarily lead to improved efficiency as more energetic squish-region vortices can lead to higher convective heat transfer losses.

42 ENGINEERING↗

Application of step-response lambda tuning to proportional-integral controllers in water resource recovery facilities

Proportional-integral-derivative (PID) controllers in water resource recovery facilities (WRRFs) feedback control loops are commonplace. While simple to implement, such control loops are rarely tuned optimally or systematically. Heuristic tuning approaches are commonly applied with varying degrees of success using trial-and-error, ad hoc tuning rules, or duplication of tuning values from a similar system. However, there are effective methods, such as lambda tuning, produce acceptable tuning with limited effort. These are based on the step-response method, where a manual process perturbation is used to define the relationship between the manipulated and controlled variables. Based on such an experiment, a simple process model is constructed and used to determine the controller tuning values. In this work, we used the step-response method and lambda tuning for two control systems in full-scale WRRFs. This led to responsive and stable behavior of the controlled system as defined by the absolute average error of the controlled variable to setpoint and standard deviation of the manipulated variable. Tuning of feedback control loops can be completed successfully through a systematic approach, and this work suggests that tuning tools, like lambda, should be part of all wastewater treatment control engineers' toolbox.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Grid generation, coupling strategies, and spatially-dependent time stepping for ocean-tidal/estuary systems and other ESM components (Final Report)

There are many multiple scale issues in the ocean modeling, including different mesh resolutions (local) and different physical processes (global). In order to gain efficiency and fidelity in modern ESMs, it is vital to develop high quality, highly nonuniform meshes and spatially-dependent time stepping strategies for coupling various climate system components. The USC/FSU team has worked on the design, analysis, and implementation of fast CVT grid generation and novel time- stepping schemes that could address all the requirements for global and regional ocean models on highly nonuniform meshes.

58 GEOSCIENCES↗