Guaranteed Element Quality Overlay Tetrahedral Mesh Generation With CAD Feature Capture.
Abstract not provided.
Staten, Matthew L.↗
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Deciding upon a Tet Meshing Approach:Searching for Guaranteed Element Quality Overlay Tetrahedral Mesh Generation With CAD Feature Capture.
Abstract not provided.
Staten, Matthew L.↗
Parallel Solver Framework for Mixed-Integer PDE-Constrained Optimization
ROL-PEBBL is a C++, MPI-based parallel code for mixed-integer PDE-constrained optimization (MIPDECO). In these problems we wish to optimize (control, design, etc.) physical systems, which must obey the laws of physics, when some of the decision variables must take integer values. ROL-PEBBL combines a code to efficiently search over integer choices (PEBBL = Parallel Enumeration Branch-and-Bound Library) and a code for efficient nonlinear optimization, including PDE-constrained optimization (ROL = Rapid Optimization Library). In this report, we summarize the design of ROL-PEBBL and initial applications/results. For an artificial source-inversion problem, finding sources of pollution on a grid from sparse samples, ROL-PEBBLs solution for the nest grid gave the best optimization guarantee for any general solver that gives both a solution and a quality guarantee.
97 MATHEMATICS AND COMPUTING↗
Enforcing central processing unit quality of service guarantees when servicing accelerator requests
Systems, apparatuses, and methods for enforcing processor quality of service guarantees when servicing system service requests (SSRs) are disclosed. A system includes a first processor executing an operating system and a second processor executing an application which generates SSRs for the first processor to service. The first processor monitors the number of cycles spent servicing SSRs over a previous time interval, and if this number of cycles is above a threshold, the first processor starts delaying the servicing of subsequent SSRs. In one implementation, if the previous delay was non-zero, the first processor increases the delay used in the servicing of subsequent SSRs. If the number of cycles is less than or equal to the threshold, then the first processor services SSRs without delay. As the delay is increased, the second processor begins to stall and its SSR generation rate falls, reducing the load on the first processor.
Basu, Arkaprava↗
Study of Different Formulations for the Multiperiod Blending Problem Applied to Lithium Recovery from Produced Water
We present several formulations to solve the MPBP for the recovery of REE/CMs from produced water and propose a decomposition approach thatleverages strategies in general disjunctive programming to enhance its performance. We compare these proposed formulations/strategies via two illustrative case studies on recovering lithium from a network of produced water sources.
Ovalle, Daniel↗
Adaptive building load control to enable high penetration of solar photovoltaic generation
This paper investigates the ability of a collection of deferrable heating, ventilation and air conditioning (HVAC) loads to directly emulate energy storage devices (ESD), that is, to absorb any low frequency fluctuations in solar generation. We find the optimal number of aggregated HVAC loads to absorb solar fluctuation in the same frequency band based on frequency analysis. To guarantee quality of service in afleet of residential buildings, an optimization problem is formed to compute optimal schedule of the HVAC loads considering temperature comfort band and available solar generation. By minimizing the tracking error between solar generation and total consumption, the proposed method also quantifies the minimum capacity of ESD (battery or fly-wheel) . The simulation results show that the proposed techniques are able to achieve good solar tracking performance as well as obtain a minimal ESD capacity. Therefore, we show that most of the renewable generation can be consumed locally through an intelligent coordination of HVAC loads, their impacts on the grid would be minimal and the required ESD capacity can be minimized.
Dong, Jin↗
Near-Optimal and Practical Algorithms for Graph Scan Statistics with Connectivity Constraints
One fundamental task in network analysis is detecting “hotspots” or “anomalies” in the network; that is, detecting subgraphs where there is significantly more activity than one would expect given historical data or some baseline process. Scan statistics is one popular approach used for anomalous subgraph detection. This methodology involves maximizing a score function over all connected subgraphs, which is a challenging computational problem. A number of heuristics have been proposed for these problems, but they do not provide any quality guarantees. Here, we propose a framework for designing algorithms for optimizing a large class of scan statistics for networks, subject to connectivity constraints. Our algorithms run in time that scales linearly on the size of the graph and depends on a parameter we call the “effective solution size,” while providing rigorous approximation guarantees. In contrast, most prior methods have super-linear running times in terms of graph size. Extensive empirical evidence demonstrates the effectiveness and efficiency of our proposed algorithms in comparison with state-of-the-art methods. Our approach improves on the performance relative to all prior methods, giving up to over 25% increase in the score. Further, our algorithms scale to networks with up to a million nodes, which is 1–2 orders of magnitude larger than all prior applications.
97 MATHEMATICS AND COMPUTING↗
Solar Buyer's Markets: Unlocking Lower Photovoltaic and Battery Prices on Online Quote Platforms
Previous NREL research shows that solar photovoltaic (PV) customers tend to obtain lower installation quote prices on online quote platforms. In new research reported in Solar Buyer's Markets: Unlocking Lower Photovoltaic and Battery Prices on Online Quote Platforms, we corroborate those results using data from the Pick My Solar quote platform. Furthermore, for the first time, we evaluate quote prices for batteries on online quote platforms. Given that few customers currently use quote platforms, we discuss various pathways to increase use of online quote platforms, including developing strategic partnerships, building customer trust, increasing market transparency, and providing quality guarantees.
14 SOLAR ENERGY↗
Robust Parameter Design on Dual Stochastic Response Models With Constrained Bayesian Optimization
In engineering system design, minimizing the variations of the quality measurements while guaranteeing their overall quality up to certain levels, namely the robust parameter design (RPD), is crucial. Recent works have dealt with the design of a system whose response-control variables relationship is a deterministic function with a complex shape and function evaluation is expensive. In this work, we propose a Bayesian optimization method for the RPD of stochastic functions. Dual stochastic response models are carefully designed for stochastic functions. The heterogeneous variance of the sample mean is addressed by the predictive mean of the log variance surrogate model in a two-step approach. We establish an acquisition function that favors exploration across the feasible and optimality-improvable regions to effectively and efficiently solve the stochastic constrained optimization problem. Further, the performance of our proposed method is demonstrated by the extensive numerical and case studies. Note to Practitioners-Many manufacturing processes involve undesirable variations, which create variations in the final products. For example, many emerging manufacturing processes, such as nanomanufacturing, involve complex physical and chemical dynamics and transformation, creating variations in the manufacturing output. In such processes, it is crucial to design the manufacturing processes or products so that they have minimum variations in their quality. Meanwhile, it is also important to maintain the overall quality of the designed processes or products. Furthermore, acquiring data from many advanced manufacturing processes is often very costly, especially in the designing stage. In this work, we propose a data-driven method that automatically finds the best setting of manufacturing processes or products with the minimum variations of quality and a given constraint on the average quality satisfied. Our proposed method is used before conducting every experiment; It analyzes the historical data from previous experiments and provides a setting to be used in the next experiment. Our proposed method efficiently utilizes the historical data, and thus finds the best robust setting by conducting only a small number of experiments.
42 ENGINEERING↗
Seawater Desalination Derived Entirely from Ocean Biomass
Solar-driven interfacial evaporation shows great prospects for seawater desalination with its rapid fast evaporation rate and high photothermal conversion efficiency. Here, a sustainable, biodegradable, non-toxic, and highly efficient full ocean biomass-based solar-driven evaporator is reported, which is composed of chitosan (CS) hydrogel as the hydratable skeleton and cuttlefish ink (CI) as the photothermal material. Under solar irradiation, the cuttlefish ink powder harvests solar energy and heats the surrounding water. Simultaneously, the water in the three-dimensional network of chitosan hydrogel is rapidly replenished by the interconnected porous structure and the hydrophilic functional groups attached to the polymer chains. With its enlarged evaporation surface, high solar absorptance, adequate water transportation, good salt drainage, and heat localization, the CI/CS-based evaporator achieves a remarkable evaporation rate of 4.1 kg m-2 h-1 under one sun irradiance (1 kW m-2) with high-quality freshwater yields. This full ocean biomass-based evaporator with abundant raw material availability provides new possibilities for an efficient, stable, sustainable, and environmentally friendly solar evaporator with guaranteed water quality.
BIOMASS FUELS,INORGANIC, ORGANIC, PHYSICAL, AND AN↗
All-quad meshing without cleanup
Here, we present an all-quad meshing algorithm for general domains. We start with a strongly balanced quadtree. In contrast to snapping the quadtree corners onto the geometric domain boundaries, we move them away from the geometry. Then we intersect the moved grid with the geometry. The resulting polygons are converted into quads with midpoint subdivision. Moving away avoids creating any flat angles, either at a quadtree corner or at a geometry–quadtree intersection. We are able to handle two-sided domains, and more complex topologies than prior methods. The algorithm is provably correct and robust in practice. It is cleanup-free, meaning we have angle and edge length bounds without the use of any pillowing, swapping, or smoothing. Thus, our simple algorithm is fast and predictable. This paper has better quality bounds, and the algorithm is demonstrated over more complex domains, than our prior version.
97 MATHEMATICS AND COMPUTING↗
A Conceptual Design and Economic Assessment of a Chitin Biorefinery Based on Shrimp Processing Wastes
Due to the extensive production of shrimp in captivity, waste generation has increased significantly and has become an environmental problem. The recovery of biomolecules can be an important way to mitigate the environmental problems associated with processing in this sector. In this sense, the present work aimed to evaluate a biorefinery approach for valuing shrimp farming waste to obtain astaxanthin, chitin and chitosan. Stoichiometric segmentation was used as a tool to identify the process steps, whose information on process variables (fresh water consumption, flow rate and reaction conditions) was adapted from the literature. A biorefinery coupled to a shrimp processing plant was proposed for the immediate use of highly perishable biomass, to guarantee the quality of the extracted products and reduce storage and transportation costs. In practice, the biomass treatment sequence adopted (demineralization followed by deproteinization) eliminates the depigmentation step, as the chitin obtained has a lighter tone. The proposed route was evaluated for four scenarios based on two indicators: gross economic potential (EGP) and metrics for inspection of sales and reagents (MISR). The results indicate that economic viability is achieved only for the production of chitosan, resulting in a gross revenue of US$832.50/cycle and a MISR value > 1. The sale of astaxanthin promotes an increase of US$3.73/cycle in the EGP, considered too low for the inclusion of another stage in the process.
astaxanthin↗
Assessing direct and indirect emissions of greenhouse gases in road transportation, taking into account the role of uncertainty in the emissions inventory
Highlights: • The use-chain model implemented in this paper is effective in minimizing uncertainty. • Data integration is important to reduce uncertainty. • An innovative metric, Emission Value at Risk, was used to adjust uncertainty values. • Indirect impacts of economic activities change the estimate of GHG emissions. - Abstract: Greenhouse gas (GHG) concentration in the atmosphere has increased since the beginning of the industrial era, with dramatic effects on climate change. Transportation is one of the main sources of GHGs, with more than two-thirds of transport-related GHG emissions attributable to road vehicles. Any policy that aims to reduce GHG emissions needs robust measuring methods that guarantee the quality and reliability of primary data and estimates. However, these estimates are subject to uncertainty, both at the stage of compiling accounting tables and at the stage of using this information to formulate a specific policy question. This paper considers how to reduce uncertainty in estimating GHG emissions from road transportation, with specific reference to a regional emissions inventory in Italy. We propose the application of a use-chain model that can tackle uncertainty in measuring GHG emissions by enhancing the quality of the emissions data registry in the inventory. This new metric, which we call emission value at risk (VaR), draws from methodologies and concepts employed in the insurance and financial sectors. Moreover, additional assessments are performed, integrating the inventory data with those available in the regional energy balance and disaggregated sectoral economic dataset. The results show that a sound accounting method enables uncertainty in emission data to be taken into account, thus improving the design of appropriate strategies to reduce GHG emissions.
54 ENVIRONMENTAL SCIENCES↗
Real-Time Optimization of Distribution-level Energy Resources [SWR-18-27]
Researchers at NREL have developed a novel real-time control architecture to optimize the operation of DERs at residential, commercial, and industrial levels. The real-time system enables (portions of) feeders to emulate virtual power plants providing services to the rest of the grid, while ensuring satisfaction of electrical limits and maximizing customers’ benefits. This system can be integrated with legacy hardware and/or new advanced systems to optimally manage both individually-controlled DERs and aggregations of DERs. By virtue of the proposed engineering approach, the DERs collectively regulate the powers at an electrical point to respond to grid dispatch signals such as an automatic generation control, a ramping signal, or a 5-minute dispatch. Overall, this architecture allows end customers to minimize their payments and partake in grid operations while guaranteeing power quality in the distribution network.
Dall-Anese, Emiliano↗
Efficient Implementation of Artificial Neural Networks for Sensor Data Analysis Based on a Genetic Algorithm
The reliability of many industrial processes depends on the sensor system. However, these sensors can be affected by noise, perturbations and failures. Hence, sensor monitoring and diagnosis are fundamental to guarantee the quality of an industrial process. Nowadays, artificial neural networks (ANN) are widely used in sensor signal processing and diagnosis. However, those ANNs usually require many artificial neurons, being difficult to implement in software and hardware due to their high computational costs. This paper presents an optimized implementation of artificial neurons in ANNs for sensor data analysis using a Genetic Algorithm (GA). The objective of GA is to find an adequate segmentation to reduce the activation function approximation error. One of the advantages of the proposed approach is that the cost function used in GA considers the effect of factors such as the ANN architecture or the number of bits used in arithmetic operations. The proposed ANN implementation technique aims to get the best possible approximation for a specific ANN architecture, making easier its implementation in software and hardware. Simulation and experimental results using FPGA (Field Programmable Gate Array) prove the advantages of the proposed approach for implementing sensor data analysis systems based on ANNs.
D estefani, André↗
Non-conformity Scores for High-Quality Uncertainty Quantification from Conformal Prediction
High-quality uncertainty quantification (UQ) is a critical component of enabling trust in deep learning (DL) models and is especially important if DL models are to be deployed in high-consequence applications. Conformal prediction (CP) methods represent an emerging nonparametric approach for producing UQ that is easily interpretable and, under weak assumptions, provides a guarantee regarding UQ quality. This report describes the research outputs of an Exploratory Express Laboratory Directed Research and Development (LDRD) project at Sandia National Laboratories. This project focused on how best to implement CP methods for DL models. This report introduces new methodology for obtaining high-quality UQ from DL models using CP methods, describes a novel system of assessing UQ quality, and provides experimental results that demonstrate the quality of the new methodology and utility of the UQ quality assessment system. Avenues for future research and discussion of potential impacts at Sandia and in the wider research community are also given.
97 MATHEMATICS AND COMPUTING↗
Technical Note: On the impact of the incident electron beam energy on the primary dose component of flattening filter free photon beams
Purpose: For commercially available linear accelerators (Linacs), the electron energies of flattening filter free (FFF) and flattened (FF) beams are either identical or the electron energy of the FFF beam is increased to match the percentage depth dose curve (PDD) of the FF beam (in reference geometry). This study focuses on the primary dose components of FFF beams for both kinds of settings, studied on the same Linac. Methods: The measurements were conducted on a VersaHD Linac (Elekta, Crawley, UK) for both FF and FFF beams with nominal energies of 6 and 10 MV. In the clinical setting of the VersaHD, the energy of FFF{sub M} (Matched) beams is set to match the PDDs of the FF beams. In contrast the incident electron beam of the FFF{sub U} beam was set to the same energy as for the FF beam. Half value layers (HVLs) and a dual parameter beam quality specifier (DPBQS) were determined. Results: For the 6 MV FFF{sub M} beam, HVL and DPBQS values were very similar compared to those of the 6 MV FF beam, while for the 10 MV FFF{sub M} and FF beams, only %dd(10){sub x} and HVL values were comparable (differences below 1.5%). This shows that matching the PDD at one depth does not guarantee other beam quality dependent parameters to be matched. For FFF{sub U} beams, all investigated beam quality specifiers were significantly different compared to those for FF beams of the same nominal accelerator potential. The DPBQS of the 6 MV FF and FFF{sub M} beams was equal within the measurement uncertainty and was comparable to published data of a machine with similar TPR{sub 20,10} and %dd(10){sub x}. In contrast to that, the DPBQS’s two parameters of the 10 MV FFF{sub M} beam were substantially higher compared to those for the 10 MV FF beam. Conclusions: PDD-matched FF and FFF beams of both nominal accelerator potentials were observed to have similar HVL values, indicating similarity of their primary dose components. Using the DPBQS revealed that the mean attenuation coefficient was found to be the same within the uncertainty of 0.8% for 6 MV FF and 6 MV FFF{sub M} beams, while for 10 MV beams, they differed by 6.4%. This shows that the DPBQS can provide a differentiation of photon beam characteristics that would remain hidden by the use of a single beam quality specifier, such as %dd(10){sub x} or HVL.
61 RADIATION PROTECTION AND DOSIMETRY↗