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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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A digital computer program is described which was developed to estimate Saturn 5 response to prelaunch wind conditions at Cape Kennedy. The program computes displacement and bending moment statistics as a function of parameters defining the atmospheric environment. A sample problem is provided to illustrate utilization of the program.
Optimal integration of thermal energy storage within commercial building applications requires accurate load predictions. Several methods exist that provide an estimate of a buildings future needs. Methods include component-based models and data-driven algorithms. This work implemented a previously untested algorithm for this application that is called a Laterally Primed Adaptive Resonance Theory (LAPART) artificial neural network (ANN). The LAPART algorithm provided accurate results over a two month period where minimal historical data and a small amount of input types were available. These results are significant, because common practice has often overlooked the implementation of an ANN. ANN have often been perceived to be too complex and require large amounts of data to provide accurate results. The LAPART neural network was implemented in an on-line learning manner. On-line learning refers to the continuous updating of training data as time occurs. For this experiment, training began with a singe day and grew to two months of data. This approach provides a platform for immediate implementation that requires minimal time and effort. The results from the LAPART algorithm were compared with statistical regression and a component-based model. The comparison was based on the predictions linear relationship with the measured data, mean squared error, mean bias error, and cost savings achieved by the respective prediction techniques. The results show that the LAPART algorithm provided a reliable and cost effective means to predict the building load for the next day.
A new guidance, steering, and control concept is described and evaluated for the Third Phase of an asymmetrical configuration of the Advanced Launch System (ALS). The study also includes the consideration of trajectory shaping issues and trajectory design as well as the development of angular rate, angular acceleration, angle of attack, and dynamic pressure estimators. The Third Phase guidance, steering and control system is based on controlling the acceleration-direction of the vehicle after an initial launch maneuver. Unlike traditional concepts, the alignment of the estimated and commanded acceleration-directions is unimpaired by an add-on load relief. Instead, the acceleration-direction steering-control system features a control override that limits the product of estimated dynamic pressure and estimated angle of attack. When this product is not being limited, control is based exclusively on the commanded acceleration-direction without load relief. During limiting, control is based on nulling the error between the limited angle of attack and the estimated angle of attack. This limiting feature provides full freedom to the acceleration-direction steering and control to shape the trajectory within the limit, and also gives full priority to the limiting of angle of attack when necessary. The flight software concepts were analyzed on the basis of their effects on pitch plane motion.
Traditional load shedding schemes can be inadequate in grids with high renewable penetration, leading to unstable events and unnecessary grid islanding. Although for both manual and automatic operating modes load shedding areas have been predefined by grid operators, they have remained fixed, and may be sub-optimal due to dynamic operating conditions. In this work, a distributed tri-level linear programming model for automatic load shedding to avoid system islanding is presented. Preventing islanding is preferred because it reduces the need for additional load shedding besides the disconnection of transmission lines between islands. This is crucial as maintaining the local generation-demand balance is necessary to preserve frequency stability. Furthermore, uneven distribution of generation resources among islands can lead to increased load shedding, causing economic and reliability challenges. This issue is further compounded in modern power systems heavily dependent on non-dispatchable resources like wind and solar. The upper-level model uses complex power flow measurements to determine the system areas to shed load depending on actual operating conditions using a spectral clustering approach. The mid-level model estimates the area system state, while the lower-level model determines the locations and load values to be shed. The solution is practical and promising for real-world applications.
Climate change can have substantial impacts on nitrogen runoff, which is a major cause of eutrophication, harmful algal blooms, and hypoxia in freshwaters and coastal regions. We examined responses of nitrate loading to climate change in the Upper Mississippi River Basin (UMRB) with an enhanced Soil and Water Assessment Tool with physically based Freeze-Thaw cycle representation (SWAT-FT), as compared with the original SWAT model that employs an empirical equation. Driven by future climate projections from five General Circulation Models (GCMs) from 1960 to 2099 under the Representative Concentrations Pathways (RCP) 8.5 scenario, we analyzed changes in riverine nitrate loadings, as well as terrestrial surface and subsurface contributions of the UMRB in the 21st century relative to the baseline period of 1960–1999. By the end of the 21st century, the original SWAT model predicted about a 50% increase in riverine nitrate loadings which is nearly twice as much as that estimated by SWAT-FT (ca. 25%). Such a large difference in projected nitrate changes can potentially mislead mitigation strategies that aim to reduce nitrogen runoff from the UMRB. Further analysis shows that the difference between the original SWAT model and SWAT-FT led to substantial discrepancies in the spatial distribution of surface and subsurface nitrate loadings in the UMRB. In general, SWAT-FT predicted more nitrate leaching for northwestern parts of the UMRB which are more sensitive to freeze-thaw cycle, mainly because SWAT-FT simulated less frequent frozen soils. This study highlights the importance of using physically based freeze-thaw cycle representation in water quality modeling. Design of future nitrogen runoff reduction strategies should include careful assessment of effects that land management has on the freeze-thaw cycles to provide reliable projection of water quality under climate change.
Residential and commercial buildings have huge potential to contribute value to improve grid resilience by participating grid services. To reveal the significant value, it is critical to estimate the grid service capability from these buildings. Unlike the large-scale distributed energy resources such as wind and solar farms, those buildings need to participate grid services in aggregation, not by individual. Therefore, it is important to appropriately group buildings for aggregation. In this paper, we develop a load profile clustering method to classify the building-level load profiles for grid service capability estimation. In our two-step clustering approach, we first calculate the total load consumption for each building, clustering the load profiles based on energy consumption level. Then, we further cluster the load profiles in each energy cluster based on the load shape. The parameter selection for each clustering step is discussed. The proposed method is applied on actual building-level load profiles, and the results have proved the effectiveness of this method.
This paper develops a flexible method for estimating the customer cost of a power outage. We add to the current body of literature by outlining a framework which properly accounts for the effects of outage duration. We begin by separating costs into categories depending on whether the cost varies with outage duration and whether the cost is due to perishable inventory. We derive useful functional forms for each cost category and discuss how parameters vary by load type and outage characteristics. We derive outage cost estimates for an unexpected loss of power to both an example manufacturing plant and an example fire station. The framework described in this paper can easily be employed to model outage costs for a wide range of specific operating conditions.
Highlights: • Standard deviation of stresses in C-S-H has the order of magnitude of the stresses applied at concrete scale. • Fluctuations increase with the stiffness and contrast of phases. • Fluctuations are dependent of mechanical load. • Transformation fields also cause mechanical fluctuations. - Abstract: Analytical homogenization provides information about the average mechanical fields but can also be used to obtain information about the statistical variability or fluctuations of these fields. Here, we present analytical estimations of the fluctuations of elastic stresses within cement-based materials (CBM). Mori-Tanaka, self-consistent and generalized self-consistent schemes are combined to represent the multiscale character of CBM. The second moment of mechanical fields is derived from the internal energy. The presence of transformation fields and resulting fluctuations are considered. We account for the evolution of the volume fractions of phases due to cement hydration. Scenarios considering or not the ITZ are studied. Our estimations are dependent on load and representation CBM microstructure. The obtained standard deviation of stresses in C-S-H are on the order of the stresses applied at concrete scale. We provide estimations of the compressive strength of a cement paste at early-age using our results of fluctuation of stresses.
A computational system for estimation of nonlinear aerodynamic characteristics of wings at supersonic speeds was developed and was incorporated in a computer program. This corrected linearized theory method accounts for nonlinearities in the variation of basic pressure loadings with local surface slopes, predicts the degree of attainment of theoretical leading edge thrust, and provides an estimate of detached leading edge vortex loadings that result when the theoretical thrust forces are not fully realized.
A high-fidelity, spatially distributed dynamic model of a supercritical pulverized coal-fired boiler was developed for calculating transient thermal profiles of the boiler tubes, which are often not measured or unmeasurable in industrial settings due to the harsh operating conditions. In this work, rigorous models of the subcritical and supercritical steam properties, which can be highly nonlinear, were used to capture the transition between two-phase and one-phase flow, respectively, as supercritical boilers frequently transition through the critical point during load-following operation. The transient boiler model was also used for data reconciliation and parameter estimation for the purpose of model validation against industrial data. An approach was developed to reduce the size of large-scale reconciliation problem by focusing on the implementation of bias terms for the reconciled variables, which can be estimated in place of the reconciled variables themselves. In addition, a functional approximation of the reconciliation problem was defined so that it can be more simply optimized. Combining this functional approximation optimization with reformulation of the reconciliation problem considering measurement biases can significantly improve the tractability of many such large-scale problems. The validated boiler model was then used to study transient responses under load-following operation with specific attention on the calculation of unmeasurable variables.
A coupled, thermal-electrochemical model is used to explain why the Joule heating assumption (i.e., I 2 R) does not provide a good representation of the temperature rise during high power pulses in lithium-ion batteries, even in cases where the reversible heat generation can be neglected. The poor agreement occurs because the internal resistance changes during the pulse due to the opposing effects of mass transport in the electrolyte, which raises the resistance, and heat generation (temperature rise), which lowers the resistance. These insights are used to propose a new analytical expression for predicting the temperature rise during adiabatic pulses with limited experimental and physical data. The expression accounts for thermal effects using a Taylor series expansion of an Arrhenius-type equation. It accounts for transport effects using an approximate solution to the one-dimensional diffusion equation. The new expression is shown to accurately estimate the simulated, adiabatic temperature rise across a range of loadings (1 to 4 mAh cm -2 ) and C-rates (1C to 10C) for cells containing LiNi 0.5 Mn 0.3 Co 0.2 O 2 positive electrodes and graphite negative electrodes. In conclusion, it is also shown to accurately estimate the experimental, adiabatic temperature rise measured for cells with LiFePO 4 positive electrodes and mesocarbon negative electrodes with minimal changes to the fitted parameters.
Several aspects of module design are evaluated, including glass superstrate and metal substrate module configurations, the potential for hail damage, light absorption in glass superstrates, the economics of glass selection, and electrical design. Also, three alternate glass superstrate module configurations are evaluated by means of finite element computer analyses. Two panel sizes, 1.2 by 2.4 m (4 by 8 ft) and 2.4 by 4.8 m are used to support three module sizes, 0.6 by 1.2 m, 1.2 by 1.2 m, and 1.2 by 2.4 m, for design loadings of + or - 1.7 kPa, + or - 2.4 kPa, and + or - 3.6 kPa. Designs and cost estimates are presented for twenty panel types and nine array configurations at each of the three design loadings. Structural cost sensitivities of combined array configurations and panel cases are presented.
Twenty pilot workload assessment techniques were compared using a simulated flying task in which three levels of psychomotor workload were imposed. The experiment was conducted in a three degree of freedom motion base simulator. Opinion measures, spare mental capacity measures, physiological measures, eye movement behavior and primary task performance measures were evaluated. The primary task was an instrument landing system (ILS) approach and landing. All measures were recorded between the outer and middle markers on the approach. Three levels of psychomotor load were obtained by the combined manipulation of wind gust disturbance level and simulated aircraft pitch stability. Six instrument rated general aviation pilots participated in the experiment. Cooper-Harper ratings, WCI/TE ratings, time estimation standard deviation, pulse rate mean, and control movements per unit time demonstrated sensitivity to psychomotor load. No intrusion into primary task performance was found that the sensitivities of workload estimation techniques vary widely, and that only a few techniques appear to be sensitive to psychomotor load.
Microgrids are an emerging alternative as an energy backup system for critical electric loads and have improved performance compared to the traditional architecture where a single emergency diesel generator is tied to an individual building. Both architectures are dependent on the reliability of their individual generators and a quantitative and realistic comparison of the overall system reliability of the two architectures is lacking. Using recently published work on emergency diesel generator finite reliability, a quantitative methodology is presented to compare the reliability of a microgrid architecture based on centralized emergency diesel generators to the traditional approach of generators tied to individual buildings. Three system reliability performance metrics are calculated as a function of outage duration: (1) probability to meet 100% of the critical load; (2) expected fraction of lost load; and (3) probability to meet the highest priority critical loads. It is shown that stand-alone building-tied emergency diesel generators systems, even when two emergency diesel generators are used per building, cannot provide the reliability required to sustain critical loads for a grid outage lasting multiple days. Due to their network configuration and ability to share load, diesel generator-based microgrid configurations are estimated to have = 93% probability of powering all buildings for a 2-week outage there the individual building-tied emergency diesel generator architecture has a =20% probability. Microgrids do present other susceptibilities that are site specific and should be considered including vulnerabilities associated with the on-campus distribution system and cybersecurity.
Using an alternative mechanism to dissipation or scattering, bistable structures and mechanical metamaterials have shown promise for mitigating the detrimental effects of impact by reversibly locking energy into strained material. Herein, we extend prior works on impact absorption via bistable metamaterials to computationally explore the dependence of kinetic energy transmission on the velocity and mass of the impactor, with strain rates exceeding 10 2 s –1 . We observe a large dependence on both impactor parameters, ranging from significantly better to worse performance than a comparative linear material. We then correlate the variability in performance to solitary wave formation in the system and give analytical estimates of idealized energy absorption capacity under dynamic loading. In addition, we find a significant dependence on damping accompanied by a qualitative difference in solitary wave propagation within the system. The complex dynamics revealed in this study offer potential future guidance for the application of bistable metamaterials to applications including human and engineered system shock and impact protection devices.
The mechanism of ethanol upgrading to higher products is still under debate, especially regarding intermediate species and hydrogenation and dehydrogenation steps. In this work, we conducted a combined theoretical and experimental approach to contribute to this discussion. For such, detailed electronic structure density functional theory calculations (aiming at probing density of states, infrared spectra, geometric parameters, charge densities, and reaction energetics) and diffuse reflectance infrared Fourier transform spectroscopy experiments were carried out revealing the relevance of an appropriate combination of reactive surface sites to support the formation of several intermediates that are formed in the C-C coupling over MgO. The roles of Mg and O sites were also studied under an electronic perspective and different geometrical arrangements. We found that a kink configuration was the most adequate for ethanol to 1-butanol upgrading. Our calculations also gave us arguments to propose distinct reaction routes, whose mutual predominance would depend upon reaction temperature. At temperatures up to 573 K, the so-called β-route, which goes through scission of a Cβ-H bond and formation of an oxametallacycle-like intermediate, would dominate the coupling, whereas at higher temperatures, up to 673 K, a more usual Guerbet mechanism, via an aldol coupling step and then consecutive hydrogenations, would be expected. Here, the theoretical conclusions were followed by a careful experimental strategy using sequential experimental planning techniques in order to estimate accurate parameters with the lowest possible experimental load. Information from these different sources were coupled to develop a mathematical model for the rate of the ethanol upgrading reaction, using a Langmuir-Hinshelwood-Hougen-Watson approach. The developed and statistically validated model adequately described the experimental data at 673 K and 1.1 bar total pressure for ethanol partial pressures in the range from 0 to 20 kPa.
Aerosol-cloud interactions remain a major uncertainty in climate research. Studies have indicated that model estimates of cloud susceptibility to aerosols frequently exceed satellite estimates, motivating model reformulations to increase agreement. Here we show that conventional ways of using satellite information to estimate susceptibility can serve as only a weak constraint on models because the estimation is sensitive to errors in the retrieval procedures. Using instrument simulators to investigate differences between model and satellite estimates of susceptibilities, we find that low aerosol loading conditions are not well characterized by satellites, but model clouds are sensitive to aerosol perturbations in these conditions. We quantify the observational requirements needed to constrain models, and find that the nighttime lidar measurements of aerosols provide a better characterization of tenuous aerosols. Here, we conclude that observational uncertainties and limitations need to be accounted for when assessing the role of aerosols in the climate system.
Viable magnetic fusion devices necessitate combining good confinement with effective power flux handling. A major concern for ITER, and devices beyond, is the divertor heat load width, which sets peak boundary heat loads on the plasma-facing materials. Current estimates of the heat flux width are narrow for future reactors. Here, we demonstrate how pedestal turbulence can expand into, or entrain, the stable scrape-off-layer and so broaden the heat flux width beyond these neoclassical predictions. Employing combined theoretical, computational, and experimental approaches, we focus on quiescent high confinement discharges on the DIII-D tokamak, but the results are of broader significance. Our findings uncover common trends in the edge turbulence intensity flux, the pressure perturbation skewness, and the turbulence mixing length, which together determine the heat flux width. This research demonstrates the physics of scrape-off-layer broadening by turbulence and highlights the promise of a turbulent pedestal for successful core-edge integration in ITER and future fusion devices.