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At least 1,099 records · Page 61

Structural Analysis of Test Flight Vehicles for Application of Multifunctional Energy Storage System

Under the NASA Aeronautics Research Mission Directorate (ARMD) Convergent Aeronautical Solutions (CAS) project, NASA Glenn Research Center has been leading Multifunctional Structures for High Energy Lightweight Load-bearing Storage (M-SHELLS) research efforts. The technology of integrating load-carrying structures with electrical energy storage capacity has the potential to reduce the overall weight of future electric aircraft. The proposed project goals were to develop M-SHELLS in the form of honeycomb coupons and subcomponents, integrate them into the structure, and conduct low-risk flight-tests onboard a remotely piloted small aircraft. Experimental M-SHELLS energy-storing coupons were fabricated and tested in the laboratory for their electrical and mechanical properties. In this report, finite element model development and structural analyses of two small test aircraft candidates are presented. The finite element analysis of the initial two-spar wing is described for strain, deflection, and weight estimation. After a test aircraft Tempest was acquired, a load-deflection test of the wing was conducted. A finite element model of the Tempest was then developed based on the test aircraft dimensions and construction detail. The component weight analyses from the finite element model and test measurements were correlated. Structural analysis results with multifunctional energy storage panels in the fuselage of the test vehicle are presented. Although the flight test was cancelled because of programmatic reasons and time constraints, the structural analysis results indicate that the mid-fuselage floor composite panel could provide structural integrity with minimal weight penalty while supplying electrical energy. To explore potential future applications of the multifunctional structure, analyses of the NASA X-57 Maxwell electric aircraft and a NASA N+3 Technology Conventional Configuration (N3CC) fuselage are presented. Secondary aluminum structures in the fuselage sub-floor and cargo area were partially replaced with reinforced five-layer composite panels with M-SHELLS honeycomb core. The N3CC fuselage weight reduction associated with each design without risking structural integrity are described. The structural analysis and weight estimation with the application of composite M-SHELLS panels to the N3CC fuselage indicate a 3.2% reduction in the fuselage structural weight, prior to accounting for the additional weight of core material required to complete the energy storage functionality.

Mukhopadhyay, Vivek↗

Recent progress in the design of the K-DEMO divertor

The preliminary conceptual design of the Korean fusion demonstration reactor (K-DEMO) with a major radius of 6.8 m and the fusion power of 2200 MW has been studied since 2012. The overall configuration of the K-DEMO divetor system based on the ITER-like water-cooled tungsten technology is a double-null type symmetric divertor subdivided into 32 toroidal modules for the vertical maintenance. A detached divertor scenario with impurity seeding was considered as the primary approach for the power exhaust to reduce the peak heat flux lower than the engineering limit of 10 MW/m 2 . The power exhaust performance at the scrap off layer was estimated by using UEDGE-2D code, a two-dimensional fluid transport code for collisional edge plasma and neutral species like N, Ne, and Ar. Particle and heat flux on inboard and outboard divertor targets were calculated for the detached cased depending on parameters such as the impurity seeding rate, pumping rate, and the pedestal density. On the other hand, a magnetic solution like X-divertor, snowflake divertor, and super X-divertor to expand the plasma wet area was considered for K-DEMO since the detached divertor increasing a radiation fraction by impurity seeding might be able to be unstable. However, the extremely high current of poloidal coils was required more than the engineering limit, 20 MA, to form magnetic field lines for the alternative divertors. Based on the physical calculation of the edge plasma, engineering analyses were carried out to find out the thermal and structural reliability. The thermo-hydraulic analysis confirmed thermal stability, whether all comprising materials are operating within their allowable temperature windows when the case of the peak heat flux is set to 10 MW/m 2 on the outboard divertor target. The response surface optimization method derived two optimal design candidates employing two kinds of heat sink materials, respectively: the reduced activation ferritic martensitic (RAFM) steel and CuCrZr alloy. Additionally, the drawbacks and merits of the two materials were definite. The optimal design with applying RAFM steel was vulnerable to withstand thermal and mechanical loads since low thermal conductivity caused too thin thickness of the heat sink. On the other hand, the CuCrZr alloy has critical drawbacks in terms of activation and radioactive waste despite its high thermal conductivity. Meanwhile, preliminary electromagnetic (EM) analysis was carried out to estimate the EM loads caused by the abnormal behaviors of plasma since EM loads are one of the most critical external loads for designing a DEMO divertor.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

H ∞ Control for Energy Dispatch in Autonomous Nanogrid With Communication Delays

This paper proposes an optimal controller and estimator for energy dispatch to balance the power supply and demand considering communication delays. The proposed algorithm involves modeling an autonomous nanogrid (ANG) consisting of distributed energy resources, energy storage systems, loads, an $H$ ∞ controller with a reference power modulation technique, and a state estimator. The ANG was developed to express the dynamic supply-demand energy balance of a nanogird system. Reference power modulation was designed to generate the desired ESS power based on the imbalanced energy. Random communication delays were modeled using a stochastic variable satisfying the Bernoulli random binary distribution. The optimal $H$ ∞ controller and estimator were developed using a linear matrix inequality approach to exponentially stabilize the closed-loop system. Simulations were performed using real daily demand forecasts obtained from the Korea Meteorological Administration to demonstrate the effectiveness of the proposed real-time optimization algorithm.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Image-based solar estimates

An example device is configured to determine, based on a sky image of a portion of sky over a power distribution network and using a convolutional neural network (CNN)-based image regression model, an estimated global horizontal irradiance (GHI) value and manage or control the power distribution network using the estimated GHI value. The device may also be configured to determine, based on GHI values and aggregate load values for at least a portion of the power distribution network, using a Bayesian Structural Time Series model, an estimated photovoltaic power output value for the at least a portion of the power distribution network. The device may manage or control the power distribution network using the estimated photovoltaic power output value.

Bernstein, Andrey↗

Large-scale Advanced Propfan (LAP) performance, acoustic and weight estimation, January, 1984

In comparison to turbo-prop applications, the Prop-Fan is designed to operate in a significantly higher range of aircraft flight speeds. Two concerns arise regarding operation at very high speeds: aerodynamic performance and noise generation. This data package covers both topics over a broad range of operating conditions for the eight (8) bladed SR-7L Prop-Fan. Operating conditions covered are: Flight Mach Number 0 - 0.85; blade tip speed 600-800 ft/sec; and cruise power loading 20-40 SHP/D2. Prop-Fan weight and weight scaling estimates are also included.

Parzych, D.↗

Estimating the Propagation of Interdependent Cascading Outages with Multi-Type Branching Processes

In this paper, the multi-type branching process is applied to describe the statistics and interdependencies of line outages, the load shed, and isolated buses. The offspring mean matrix of the multi-type branching process is estimated by the Expectation Maximization (EM) algorithm and can quantify the extent of outage propagation. The joint distribution of two types of outages is estimated by the multi-type branching process via the Lagrange-Good inversion. The proposed model is tested with data generated by the AC OPA cascading simulations on the IEEE 118-bus system. The largest eigenvalues of the offspring mean matrix indicate that the system is closer to criticality when considering the interdependence of different types of outages. Compared with empirically estimating the joint distribution of the total outages, good estimate is obtained by using the multitype branching process with a much smaller number of cascades, thus greatly improving the efficiency. It is shown that the multitype branching process can effectively predict the distribution of the load shed and isolated buses and their conditional largest possible total outages even when there are no data of them.

97 MATHEMATICS AND COMPUTING↗

A Universal Algorithm for the Detection of Bi-directional Gage Output Characteristics

A universal algorithm was developed that may be used to assess the bi-directional characteristics of the gage outputs of a wind tunnel strain-gage balance. The algorithm assumes that balance loads and gage outputs are described in the design format of the balance. It can also be applied to balance calibration data that is processed by using either the Iterative Method or the Non-Iterative Method. The algorithm uses an estimate of the bi-directional part of a gage output at load capacity as input. In addition, the statistical significance of the principle absolute value term in the regression model of either the gage output or the related primary load component is determined. A gage output is assumed to be bi-directional if two conditions are fulfilled: the bi-directional part of the output at load capacity exceeds 0.5 percent of the maximum output at load capacity; the p-value of the principle absolute value term of the regression model of the balance data is less than the threshold of 0.001. Data from the calibration of two six-component force balances and one five-component semi-span balance are used to illustrate the application of the universal detection algorithm.

wind tunnel test↗

Preliminary Thermal Modeling of HI-STORM 100 Storage Modules at Diablo Canyon Power Plant ISFSI

Thermal analysis is being undertaken at Pacific Northwest National Laboratory (PNNL) in support of inspections of selected storage modules at various locations around the United States, as part of the Used Fuel Disposition Campaign of the U.S. Department of Energy, Office of Nuclear Energy (DOE-NE) Fuel Cycle Research and Development. This report documents pre-inspection predictions of temperatures for two modules at the Diablo Canyon Power Plant ISFSI identified as candidates for inspection. These are HI-STORM 100 modules of a site-specific design for storing PWR 17x17 fuel in MPC-32 canisters. The temperature predictions reported in this document were obtained with detailed COBRA-SFS models of these storage systems, with the following boundary conditions and assumptions. • storage module overpack configuration based on FSAR documentation of HI-STORM100S-218, Version B; due to unavailability of site-specific design data for Diablo Canyon ISFSI modules • Individual assembly and total decay heat loadings for each canister, based on at-loading values provided by PG&E, “aged” to time of inspection using ORIGEN modeling - Special Note: there is an inherent conservatism of unquantified magnitude – informally estimated as up to approximately 20% -- in the utility-supplied values for at-loading assembly decay heat values • Axial decay heat distributions based on a bounding generic profile for PWR fuel. • Axial location of beginning of fuel assumed same as WE 17x17 OFA fuel, due to unavailability of specific data for WE17x17 STD and WE 17x17 Vantage 5 fuel designs • Ambient conditions of still air at 50°F (10°C) assumed for base-case evaluations - Wind conditions at the Diablo Canyon site are unquantified, due to unavailability of site meteorological data - additional still-air evaluations performed at 70°F (21°C), 60°F (16°C), and 40°F (4°C), to cover a range of possible conditions at the time of the inspection. (Calculations were also performed at 80°F (27°C), for comparison with design basis assumptions.) All calculations are for steady-state conditions, on the assumption that the surfaces of the module that are accessible for temperature measurements during the inspection will tend to follow ambient temperature changes relatively closely. Comparisons to the results of the inspections, and post-inspection evaluations of temperature measurements obtained in the specific modules, will be documented in a separate follow-on report, to be issued in a timely manner after the inspection has been performed.

Site Inspection↗

Master State Distributed Estimator (masde)

The MSE technology provides a distributed state estimation scheme for power utilities by making it a real time dynamic system, versus the static snapshot method used today. This will allow utilities to verify power grid readings and identify false data on the communication network. The prevailing method of estimation takes all the data from the system into a single load flow equation at the utilities command center. This becomes a large algorithm that is very time consuming to solve, providing the engineers only snap shots of the system. The MFD distributes an algorithm to devises that are already installed at various locations on the power grid. This allows for much faster computer times because the algorithms contain magnitudes less data. When each distributed estimator completes its calculation, it sends the results back to the master device to check against all other distributed estimators.

Reen, DylanW.↗

Window Attachments: The Next Big Energy-Savings Measure?

Windows in residential buildings are estimated to generate 29% of all HVAC heating and cooling load, approximately 2.67 quadrillion Btu (Apte and Arasteh 2006). Although more than a third of residential windows are single pane, very few utility programs offer incentives for installation of energy-efficient windows (Bickel et al. 2013). The reason is simple: unless someone is already planning to replace their windows, the payback can often take a decade, if not longer. Preliminary data indicates that some energy-efficient window attachments, such as low- emissivity (low-e) storm windows and interior panels, cellular shades, interior and exterior roller shades and shutters, window films, solar screens, window quilts, and awnings, can deliver cost-effective energy savings. Additionally, the means to reliably identify and compare energy-efficient window attachment products will soon be available through the Attachment Energy Rating Council (AERC), a public interest energy performance rating and certification organization co-funded by the U.S. Department of Energy (DOE) and the window attachment industry. This paper presents, for the first time, national and regional energy savings estimates for cellular shades and low-emissivity storm windows and panels using existing data on household energy savings potential. This paper is an early step in the process of determining the cost-effectiveness of window attachments for utility programs. The next step is for utilities to develop pilot programs to conduct field tests of these products, which will generate the energy savings data to determine if full-scale programs are cost-effective.

Bickel, Stephen↗

A Test Bed for Evaluating Frequency Estimation Algorithms in Synthetic Inertia Control: User Manual

As penetration of converter interfaced generators (CIGs) increases, the need for CIG frequency control participation increases. Traditionally, research in this area has been performed using positive sequence simulation software, which provides voltage magnitude and phase measurements, but not point-on-wave (POW) measurements. This means that the effect of frequency estimation algorithms cannot be accurately modeled, especially when the voltage waveform is distorted by faults or load connection events. This report serves as a user manual for an electromagnetic transient simulation testbed, which allows for accurate modeling of frequency estimation and control techniques.

42 ENGINEERING↗

Robust Medium-Voltage Distribution System State Estimation using Multi-Source Data

Due to the lack of sufficient online measurements for distribution system observability, pseudo-measurements from short-term load or distributed renewable energy resources (DERs) forecasting are used. However, the accuracy of them is low and thus significantly limits the performance of distribution system state estimation (DSSE). In this paper, a robust DSSE that integrates multi-source measurement data is proposed. Specifically, the historical low-voltage (LV) side smart meters are used to forecast load and DERs injections via the support vector machine (SVM) with optimally tuned parameters. By contrast, the online smart meters at LV side are utilized to derive equivalent power injections at the MV/LV transformers, yielding more accurate pseudo-measurements compared to the forecasted injections. Furthermore, to deal with bad data caused by communication loss, instrumental errors and cyber attacks, robust DSSE that relies on generalized maximum-likelihood (GM)-estimation criterion is developed. The projection statistics are developed to adjust the weights of each measurement, leading to better balance between pseudo- and real-time measurements. Numerical results conducted on modified IEEE 33-bus system with DG integration demonstrate the effectiveness and robustness of the proposed method.

distribution system state estimation↗

A Data-Driven Nonparametric Approach for Probabilistic Load-Margin Assessment Considering Wind Power Penetration

A modern power system is characterized by an increasing penetration of wind power, which results in large uncertainties in its states. These uncertainties must be quantified properly; otherwise, the system security may be threatened. Facing this challenge, here we propose a cost-effective, data-driven approach to assessing a power system's load margin probabilistically. Using actual wind data, a kernel density estimator is applied to infer the nonparametric wind speed distributions, which are further merged into the framework of a vine copula. The latter enables us to simulate complex multivariate and highly dependent model inputs with a variety of bivariate copulae that precisely represent the tail dependence in the correlated samples. Furthermore, to reduce the prohibitive computational time of traditional Monte-Carlo simulations that process a large amount of samples, we propose to use a nonparametric, Gaussian-process-emulator-based reduced-order model to replace the original complicated continuation power-flow model through a Bayesian-learning framework. To accelerate the convergence rate of this Bayesian algorithm, a truncated polynomial chaos surrogate, which serves as a highly efficient, parametric Bayesian prior, is developed. This emulator allows us to execute the time-consuming continuation power-flow solver at the sampled values with a negligible computational cost. Results of simulations that are performed on several test systems reveal the impressive performance of the proposed method in the probabilistic load-margin assessment.

17 WIND ENERGY↗

Aerosol optical, microphysical, chemical and radiative properties of high aerosol load cases over the Arctic based on AERONET measurements

Columnar mass concentrations of aerosol components over the Arctic are estimated using microphysical parameters derived from direct sun extinction and sky radiance measurements of Aerosol Robotic Network. Aerosol optical, microphysical, chemical and radiative properties show that Arctic aerosols are dominated by fine mode particles, especially for high aerosol load cases. The average aerosol optical depth (AOD) of the selected Arctic sites in the sampling period is approximately 0.08, with 75% composed of fine mode particles. The fine mode fraction mostly exceeds 0.9 when AOD greater than 0.4. The ammonium sulfate-like component (AS) contributes about 68% of total dry aerosol mass for high-AOD events. The estimated compositions and back trajectories show that the transported aerosol particles from biomass burning events have large amounts of black carbon (BC) and brown carbon, while those from pollution events are characterised by large AS fractions. The instantaneous radiative forcing at the top-of-atmosphere is higher for the more absorbing components, and varies greatly with surface albedo and solar zenith angle. A regression model of columnar composition and radiative forcing within the atmosphere (RFATM) for Arctic aerosol is established, showing that BC dominates a positive RFATM with a high warming efficiency.

54 ENVIRONMENTAL SCIENCES↗

Displacements of the earth's surface due to atmospheric loading - Effects of gravity and baseline measurements

Atmospheric mass loads and deforms the earth's crust. By performing a convolution sum between daily, global barometric pressure data and mass loading Green's functions, the time dependent effects of atmospheric loading, including those associated with short-term synoptic storms, on surface point positioning measurements and surface gravity observations are estimated. The response for both an oceanless earth and an earth with an inverted barometer ocean is calculated. Load responses for near-coastal stations are significantly affected by the inclusion of an inverted barometer ocean. Peak-to-peak vertical displacements are frequently 15-20 mm with accompanying gravity perturbations of 3-6 micro Gal. Baseline changes can be as large as 20 mm or more. The perturbations are largest at higher latitudes and during winter months. These amplitudes are consistent with the results of Rabbel and Zschau (1985), who modeled synoptic pressure disturbances as Gaussian functions of radius around a central point. Deformation can be adequately computed using real pressure data from points within about 1000 km of the station. Knowledge of local pressure, alone, is not sufficient. Rabbel and Zschau's hypothesized corrections for these displacements, which use local pressure and the regionally averaged pressure, prove accurate at points well inland but are, in general, inadequate within a few hundred kilometers of the coast.

Van Dam, T. M.↗

The Effect of Pre-Stressing on the Static Indentation Load Capacity of the Superelastic 60NiTi

Superelastic nickel-titanium alloys, such as 60NiTi (60Ni-40Ti by wt.%), are under development for use in mechanical components like rolling element bearings and gears. Compared to traditional bearing steels, these intermetallic alloys, when properly heat-treated, are hard but exhibit much lower elastic modulus (approx.100 GPa) and a much broader elastic deformation range (approx.3 percent or more). These material characteristics lead to high indentation static load capacity, which is important for certain applications especially space mechanisms. To ensure the maximum degree of elastic behavior, superelastic materials must be pre-stressed, a process referred to as "training" in shape memory effect (SME) terminology, at loads and stresses beyond expected use conditions. In this paper, static indentation load capacity tests are employed to assess the effects of pre-stressing on elastic response behavior of 60NiTi. The static load capacity is measured by pressing 12.7 mm diameter ceramic Si3N4 balls into highly polished, hardened 60NiTi flat plates that have previously been exposed to varying levels of pre-stress (up to 2.7 GPa) to determine the load that results in shallow but measurable (0.6 m, 25 in. deep) permanent dents. Hertz stress calculations are used to estimate contact stress. Without exposure to pre-stress, the 60NiTi surface can withstand an approximately 3400 kN load before significant denting (>0.4 m deep) occurs. When pre-stressed to 2.7 GPa, a static load of 4900 kN is required to achieve a comparable dent, a 30 percent increase. These results suggest that stressing contact surfaces prior to use enhances the static indentation load capacity of the superelastic 60NiTi. This approach may be adaptable to the engineering and manufacture of highly resilient mechanical components such as rolling element bearings.

DellaCorte, Christopher↗

Post-Flight Sampling and Loading Characterization of Trace Contaminant Control Subassembly Charcoal

Trace chemical contaminants produced by equipment offgassing and human metabolic processes are removed from the atmosphere of the International Space Station s U.S. Segment by a trace contaminant control subassembly (TCCS). The TCCS employs a combination of physical adsorption, thermal catalytic oxidation, and chemical adsorption processes to accomplish its task. A large bed of granular activated charcoal is a primary component of the TCCS. The charcoal contained in this bed, known as the charcoal bed assembly (CBA), is expendable and must be replaced periodically. Pre-flight engineering analyses based upon TCCS performance testing results established a service life estimate of 1 year. After nearly 1 year of cumulative in-flight operations, the first CBA was returned for refurbishment. Charcoal samples were collected and analyzed for loading to determine the best estimate for the CBAs service life. A history of in-flight TCCS operations is presented as well as a discussion of the charcoal sampling procedures and chemical analysis results. A projected service life derived from the observed charcoal loading is provided. Recommendations for better managing TCCS resources are presented.

Perry, J. L.↗