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At least 91 records · Page 5

MArVD2: a machine learning enhanced tool to discriminate between archaeal and bacterial viruses in viral datasets

Abstract Our knowledge of viral sequence space has exploded with advancing sequencing technologies and large-scale sampling and analytical efforts. Though archaea are important and abundant prokaryotes in many systems, our knowledge of archaeal viruses outside of extreme environments is limited. This largely stems from the lack of a robust, high-throughput, and systematic way to distinguish between bacterial and archaeal viruses in datasets of curated viruses. Here we upgrade our prior text-based tool (MArVD) via training and testing a random forest machine learning algorithm against a newly curated dataset of archaeal viruses. After optimization, MArVD2 presented a significant improvement over its predecessor in terms of scalability, usability, and flexibility, and will allow user-defined custom training datasets as archaeal virus discovery progresses. Benchmarking showed that a model trained with viral sequences from the hypersaline, marine, and hot spring environments correctly classified 85% of the archaeal viruses with a false detection rate below 2% using a random forest prediction threshold of 80% in a separate benchmarking dataset from the same habitats.

Vik, Dean (ORCID:000000027546899X)↗

An Error Analysis Toolkit for Binned Counting Experiments

We introduce the MINERvA Analysis Toolkit (MAT), a utility for centralizing the handling of systematic uncertainties in HEP analyses. The fundamental utilities of the toolkit are the MnvHnD, a powerful histogram container class, and the systematic Universe classes, which provide a modular implementation of the many universe error analysis approach. These products can be used stand-alone or as part of a complete error analysis prescription. They support the propagation of systematic uncertainty through all stages of analysis, and provide flexibility for an arbitrary level of user customization. This extensible solution to error analysis enables the standardization of systematic uncertainty definitions across an experiment and a transparent user interface to lower the barrier to entry for new analyzers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Topological photonic crystal fiber

Photonic crystal fibers (PCFs) provide a versatile platform for various applications, thanks to the flexibility with which light guiding can be customized by modifying the fiber geometry. We realize a PCF with guided modes produced by photonic band structure topology rather than conventional mode-trapping mechanisms. The design, which is compatible with the stack-and-draw fabrication process, consists of a cross-sectional photonic topological crystalline insulator with a disclination. A bulk-defect correspondence produces degenerate topological modes, lying below the cladding light line. We use various theoretical methods to confirm their topological origins, including a spectral localizer that makes minimal assumptions about the band structure. Our experiments on the fabricated fiber show it transmitting visible to near-infrared light with low losses of 10 to 20 decibels per kilometer, which do not increase substantially when the fiber is bent. A comparable solid-core PCF of conventional design exhibits substantially higher bending losses. Optical fibers based on topological modes hold promise for improved performance and versatile functionalities.

Zhu, Bofeng [Nanyang Technological Univ. (Singapor↗

Exascale-Enabled Models and Algorithms for Microelectronics Applications (MicroEleX) v1

The MicroEleX code package contains a variety of models and algorithms for physical modeling of microelectronic circuitry, including electrostatics, electrodynamics, superconducting physics, micromagnetics, multi-ferroic systems, and quantum transport. MicroEleX leverages the AMReX software framework to provide scalability on GPU-based supercomputing architectures. The code is open source and designed to be algorithmically flexible so developers can incorporate enhanced or customized physics.

Nonaka, Andy↗

Designing a transactive electric vehicle agent with customer’s participation preference

The proliferation of electric vehicles (EVs) and their inherent flexibility in charging timings make them an asset to improve grid performance. In contrast to direct control by a utility or autonomous price-based charging, the transactive control framework not only provides benefits to both grid and customers but also ensures customer autonomy. In this work, we design a transactive electric vehicle (TEV) agent that incorporates the EV owner’s willingness to trade-off between savings and amenity in form of a slider, where the EV owner’s amenity is characterized as vehicle readiness. Further, a privacy-preserving bidding formulation is proposed that also represents the customer’s transactive preference. A transactive market mechanism is discussed that integrates the TEV Agents into the local retail market and reconciles with the current day-ahead and real-time market structure. It is demonstrated that the proposed slider is able to provide a preferred trade-off between savings and amenity to individual customers. At the same time, the market mechanism is shown to successfully reduce both peak prices and peak demand. A comparative investigation of V1G and V2G technologies with respect to the battery prices is also discussed. It reveals that the V2G does not offer significant additional benefits with current battery prices, but could be promising if battery costs decline in the future.

33 ADVANCED PROPULSION SYSTEMS↗

Dataset for: Price Controls for Scarcity Events in Real-Time and Transactive Energy Systems

Real time pricing (RTP) is often promoted as a mechanism to improve the economic efficiency of the electricity system. However, many regulators have been hesitant to adopt RTP due to concerns about exposing customers to extreme price swings. To balance these concerns, this paper proposes a methodology for establishing price controls, based on the supply of demand-side flexibility in the system. As an illustrative example, we measure price responsiveness using an agent-based simulation model that is representative of the ERCOT market. The model is composed of a distribution feeder that has 250 customers with active agents controlling their HVAC systems in response to the historical ERCOT RTP with an artificially added high-price event. These agents are subjected to increasing electricity prices during the event, which we then use to create a supply curve for demand-side resources in our modeled scarcity event. We set potential price caps at points on the supply curve where customers’ have exhausted their flexible capacity. Using historical prices, we examine the systemic costs of these price caps, and present regulatory options for recouping them. Utilities and regulators interested in limiting consumer risk from dynamic pricing can utilize these methods to develop rate structures and encourage conservation. The attached data upload allows for the duplication or modification of the analysis performed in this study.

Kerby, Jessica R↗

Reducing Grid Costs while Abating Emissions: Opportunities for Flexible Building Loads

This study evaluates the value of technology-agnostic, shiftable flexible building loads in modeled 2030 and 2040 U.S. grids for four types of customers under three potential aggregated distributed energy resources programs. The value examined includes monetary value from providing grid services (e.g., energy, capacity, flexibility reserve, regulation reserve, contingency reserve) and from reducing greenhouse gas emissions. By comparing more than 845,164,800 simulated shifting opportunities, the study finds that the timing of consumption is critical for profit-driven customers. A program that is activated for 30 critical hours of system operation can result in to $73 per year in revenue for 1 kWh of shiftable load. Emission reduction, on the other hand, is best accumulated through a year-round program: 1 kWh of shiftable load can lead to up to 487.9 kg CO2e carbon reduction per year. The report also provides detailed insights on the trade-off between revenue and emissions, regional variation, short- versus medium- term value, and impacts from various building flexibility parameters, such as shifting window and dissipation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

URBANopt: An Open-Source Software Development Kit for Community and Urban District Energy Modeling: Preprint

Urban building modeling tools are developing rapidly; these tools use emerging simulation workflows for specific urban environmental design tasks, such as assessing the impacts of energy efficiency technologies at a district scale. However, with the emergence of new environmental design tasks, addressing all possible use cases and tasks is challenging and cannot be covered by a single tool. Urban-scale analysis at this level of complexity often requires linking multiple emerging tools, rather than using a single tool, to adequately evaluate a variety of possible fields in urban environmental design. To achieve this, flexible platforms are needed to support multiple input formats (e.g., geometric and non-geometric building properties), enabling the mapping of such inputs to underlying simulation engines. This paper provides an overview of the open-source URBANopt Software Development Kit (SDK) for modeling high-performance buildings and energy systems at a district scale. URBANopt's flexible SDK is composed of several modules that can be customized to integrate with other tools and generate new workflows to perform urban environmental design tasks, such as capturing interactions between individual buildings, district energy systems, distributed energy resources, and the electric distribution grid. We describe the functionality of the core SDK modules in URBANopt (called Core Gem, GeoJSON Gem, and Scenario Gem) and discuss the flexibility of these modules as a means of integration with a variety of tools. We also document and demonstrate technical details of writing and combining new modules to create customized workflows. Finally, we present a case study that uses the URBANopt SDK to model a hypothetical mixed-use urban project and simulate various scenarios to meet district energy performance goals.

buildings↗

MultiPhATE2: code for functional annotation and comparison of phage genomes

To address a need for improved tools for annotation and comparative genomics of bacteriophage genomes, we developed multiPhATE2. As an extension of multiPhATE, a functional annotation code released previously, multiPhATE2 performs gene finding using multiple algorithms, compares the results of the algorithms, performs functional annotation of coding sequences, and incorporates additional search algorithms and databases to extend the search space of the original code. MultiPhATE2 performs gene matching among sets of closely related bacteriophage genomes, and uses multiprocessing to speed computations. MultiPhATE2 can be re-started at multiple points within the workflow to allow the user to examine intermediate results and adjust the subsequent computations accordingly. In addition, multiPhATE2 accommodates custom gene calls and sequence databases, again adding flexibility. MultiPhATE2 was implemented in Python 3.7 and runs as a command-line code under Linux or MAC operating systems. Full documentation is provided as a README file and a Wiki website.

59 BASIC BIOLOGICAL SCIENCES↗

SYMBIOSYS: A Methodology for Performance Analysis of Composable HPC Data Services

Microservices are a powerful new way of building, customizing, and deploying distributed services owing to their flexibility and maintainability. Several large-scale distributed platforms have emerged to serve the growing needs of data-centric workloads and services in commercial computing. Concurrently, high-performance computing (HPC) systems and software are rapidly evolving to meet the demands of diversified applications and heterogeneity. The interplay of hardware factors, software configuration parameters, and the flexibility offered with a microservice architecture makes it nontrivial to estimate the optimal service instantiation for a given application workload. Further, this problem is exacerbated when considering that these services operate in a dynamic and heterogeneous HPC environment. An optimally integrated service can be vastly more performant than a haphazardly integrated one. Existing performance tools for HPC either fail to understand the request-response model of communication inherent to microservices or they operate within a narrow scope, limiting the insight that can be gleaned from employing them in isolation. We propose a methodology for integrated performance analysis of HPC microservices frameworks and applications called SYMBIOSYS. We describe its design and implementation within the context of the Mochi framework. This integration is achieved by combining distributed callpath profiling and tracing with a performance data exchange strategy that collects fine-grained, low-level metrics from the RPC communication library and network layers. The result is a portable, low-overhead performance analysis setup that provides a holistic profile of the dependencies among microservices and how they interact with the Mochi RPC software stack. Using HEPnOS, a production-quality Mochi data service, we demonstrate the low-overhead operation of SYMBIOSYS at scale and use it to identify the root causes of poorly performing service configurations.

microservices↗

UFO 2.0: the ‘Universal Feynman Output’ format

Abstract We present an update of the Universal FeynRules Output model format, commonly known as the UFO format, that is used by several automated matrix-element generators and high-energy physics software. We detail different features that have been proposed as extensions of the initial format during the last ten years, and collect them in the current second version of the model format that we coin the Universal Feynman Output format. Following the initial philosophy of the UFO, they consist of flexible and modular additions to address particle decays, custom propagators, form factors, the renormalisation group running of parameters and masses, and higher-order quantum corrections.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Development of an Enhanced Radiation Physics Toolset for Modeling Spectral and Imaging Signatures in the Warm Dense Matter Experiments

Radiative and atomic processes in plasmas play a critical role in a wide variety of high energy density laboratory plasma (HEDLP) experiments. The emission, absorption, and transport of radiation can strongly affect the overall energetics and evolution of such plasmas. In addition, radiation-based diagnostics – including imaging, spectroscopy, and absolute flux measurements – are widely used to determine key features of HEDLPs. To advance our understanding of HEDLP science, it is vital to have high-fidelity computational physics tools that have well-tested radiation physics modeling, and that are readily accessible to researchers in the HEDLP community. Simulations play an extremely important role for planning and designing the experiments, as well as for post-experiment data analysis. Prism Computational Sciences develops software that is used by National Laboratories and universities (including five members of LaserNetUS network). Prominent examples of such research efforts include z-pinch and short-pulse laser experiments designed to study the basic physics of photoionized plasmas and photoionization fronts, as well as their application to astrophysical plasmas. The main effort was dedicated to the development of non-equilibrium equation-of-state (EOS) models within the HELIOS-CR code, a hydrodynamics code with inline collisional-radiative atomic kinetics. Gas cell experiments on Z and Omega demonstrated the importance of non-equilibrium effects on atomic kinetics in photoionized plasmas. Recent proof-of-principle experiments on Omega EP confirmed the advantages of using a short-pulse laser to create an intense radiation drive, leading to additional experiments being proposed. Photoionization front experiments at LLE also emphasizes the importance of radiation and atomic physics. In both studies, HELIOS-CR simulations played a crucial role in computing non-equilibrium opacities and ionization distributions. A newly developed non-LTE EOS model will help addressing possible non-equilibrium effects, on for example specific heat, and their influence in plasma evolution. Prism also implemented support for open-source atomic data generated by the Flexible Atomic Code. This allows researchers to generate custom atomic tables and use them within the complex framework of simulation tools developed by Prism. The ability to use open-source atomic data would be extremely valuable for hydrodynamics and spectroscopic simulations that include high-Z materials, e.g., picosecond x-ray pulse generation experiments. Support for new atomic structures was fully implemented, and the data can be used by all simulation tools developed at Prism: radiation-hydrodynamics, imaging and spectroscopy, EOS and opacity. The development resulted in a significant fidelity enhancement to the simulations tools developed by Prism that are currently used in other cutting-edge experiments including: opacity measurement experiments performed to both understand the basic radiative and atomic properties of plasmas as well as provide data for more accurately modeling the internal structure of the Sun and other stars, high-intensity short-pulse laser experiments performed to develop short-wavelength light sources for use as backlighters and to investigate fast ignition concepts for inertial fusion energy; capsule implosion experiments designed to develop inertial fusion as an energy source, etc.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Cold Spray Additive Manufacturing For New Pipeline Fabrication In Live, Natural Gas Distribution Mains

ULC Technologies (ULC) and the Penn State University Applied Research Lab (PSU ARL) developed a process and approach for rehabilitating live, natural gas distribution pipelines using Cold Spray Additive Manufacturing (CSAM). Robotic inline fabrication of a new pipe will be performed inside a natural gas main without disrupting customers. The material studied was blended with stainless steel which offers corrosion resistance, high strength and compatibility with hydrogen to enable a robust pipeline system that is future proofed. Stainless steel coatings sprayed and tested in the lab showed excellent strength, ductility, and porosity values. ULC initially sought to use methane as the process gas for compatibility with the host pipe, but after evaluating the field and lab challenges, nitrogen was deemed to be more suitable. Early robotic concepts have been developed that indicate technical feasibility. While the technology development originally targeted natural gas distribution mains, market research showed a broader need. Spot repairs performed in natural gas transmission mains may be a more economical approach for reinforcing distribution and transmission mains compared with full pipe-in-pipe rehabilitation. Additive manufacturing offers custom programming, as well as high accuracy and precision. This means custom contours can be manufactured in situ, offering flexibility in the repair solution, such as fabricating internal full circumferential sleeves. The value of the repair can be high at difficult-to-reach locations and in pipes that need reinforcement before the injection of methane-hydrogen blends.

03 NATURAL GAS↗

Sustainable Polymer for Polyolefin Replacement (CRADA Final Report)

Sustainable Chemicals, LLC (Participant, Sust-Chem) develops renewable, biodegradable bioplastics for the replacement of large-volume petrochemical plastics such as polyethylene (PE) and polypropylene (PP). Participant’s patented bioplastics will find use in everyday items such as plastic bags, flexible containers, packaging, and toys and will address customers' ask for goods that are sustainable but don't cost a premium. Participants’ plastic comes from plant biomass and at the end of its lifecycle, is compostable or chemically recyclable. During the CRADA, Participant and Contractor will jointly refine the polymerization process used to make our bioplastic. Participant and Contractor will focus on technologies that are economically and industrially feasible, complete with full polymer characterization.

36 MATERIALS SCIENCE↗

Design trade-offs for residential retail tariffs and virtual power plants

Retail rate design and virtual power plants (VPPs) have the potential to shift customer electricity demand and provide economic benefits to utility customers. As the adoption of distributed energy resources (DERs) and flexible loads increases, retail tariff and program design can impact Bonbright's rate design principles including affordability, fairness, and economic efficiency. We model the effects of residential retail rates and VPP programs on power system costs in Massachusetts under a potential future system with high renewable energy and DER adoption. We model interactions among retail rate design, demand flexibility, and utility costs and identify trade-offs across different rate designs and VPP programs. We estimate that time-of-use (TOU) rates and VPP programs designed to avoid critical peak rates can lower overall system costs by 3.5 %-4.8 %. These lower costs translate to lower electricity bills for 62 %-91 % of customers, depending on the scenario. Although TOU rates with a critical peak VPP program can benefit all customer segments and are economically efficient, a VPP program with flat rates leads to the lowest overall bills for customers. We find that customers with loads that align with peak demand and who participate in critical peak VPP programs can underpay for their contribution to utility costs and shift costs to other customers. While our assumptions about mandatory TOU and/or critical peak pricing likely impact the magnitude of the results, the results highlight the trade-offs of these tariffs and programs and the importance of tariff and program design as demand becomes more flexible and responsive.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Demonstrating Load-Shaping Capabilities of Cost Minimizing Heat Pump Water Heater Controls with Varying Price Profiles

Increased penetration of photovoltaics and electrification of traditionally gas appliances are exacerbating existing challenges in cost-effectively balancing electricity grid supply and demand. Decarbonization without incurring expensive transmission and distribution system capacity increases requires shifting building loads from peak demand times to peak renewable production times. Grid operators are evaluating new ways of encouraging load shifting, including using time-varying price structures to provide a financial incentive. If devices incorporate price-responsive controls, a price profile could be designed to yield a wide variety of load curves as needed to optimize grid functionality. Heat pump water heaters (HPWHs) are an ideal device for price-responsive controls because the storage tank enables them to optimize the timing of electricity consumption without impacting hot water delivery service. This paper presents work demonstrating how price-responsive controls for HPWHs can provide different load profiles, as needed to stabilize the grid, in response to different price profiles. HPWH manufacturers now include web API and CTA-2045 communication capabilities which enable sending load shaping control signals. Pilot studies and preliminary programs have utilized these capabilities with uniform control strategies to reduce 4-9 PM electricity consumption. However, no studies have developed flexible controls capable of both a) responding to constantly varying price profiles and b) customizing logic to match the needs of each HPWH. Berkeley Lab's CalFlexHub project is pioneering price-driven load flexibility by developing and deploying cost-minimizing controls utilizing setpoint setting signals for fleets of HPWHs in response to varying price profiles. Control development is based on simulations using the Flexible Heat Pump Water Heater Performance Predictor which captures the control decisions of a residential, integrated HPWH manufacturer’s on-board controller. The proposed cost-reducing controls respond to constantly changing price profiles, providing the ability to change the price profile to generate load curves as needed to maintain grid stability. Preliminary simulations studying the load shaping capabilities of price-responsive controls on a fleet of 60 HPWHs have demonstrated an average of a) 135.4% increases in load during low-price periods, b) >36.8% reductions in electricity peak-price period, and c) 6.2% electricity cost savings.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Quantifying the effect of multiple load flexibility strategies on commercial building electricity demand and services via surrogate modeling

The expansion of commercial building demand response as a demand-side management resource for the electric grid necessitates new decision support resources for customers seeking to assess the benefit–risk tradeoffs of possible strategies for energy flexible building operations. To address this need, we, in this study, develop surrogate models that predict the impacts of several load flexibility strategies on commercial building electricity demand and indoor temperature, focusing on offices and retail buildings at multiple scales. The surrogate models are fit to a synthetic database generated via whole building simulations, which establish the relationships between the key operational features of a given strategy and potential changes in building demand and temperature across a variety of contexts. The surrogate models are translated to a Bayesian framework to allow straightforward communication of uncertainty and parameter updating given new evidence. We find strong predictive performance across the suite of models, underscoring the usefulness of the approach in guiding decisions about implementing load flexibility strategies under a particular set of operational and environmental conditions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Robust bidding strategy for aggregation of distributed prosumers in flexiramp market

Distributed prosumers (DPs) are the grid customers that own energy production/storage assets. Due to the flexibility and fast response of their assets, they can procure ancillary service products (ASP) in the wholesale market. An appealing ASP offered by California ISO in the real-time market (RTM) is flexiramp for which market participants do not submit direct offers, and the compensation is based on their energy opportunity costs. Here in this report, we propose a bidding strategy model for DP aggregator participation in the RTM considering energy and flexiramp. First, we develop a risk-averse optimization to determine the optimal energy and reserve product to trade in day-ahead market while considering proper amounts of flexiramp to trade in the RTM. In the RTM, to obtain optimal amounts of energy and flexiramp, the aggregator must submit hourly multi-level price-quantity energy bids for multiple RTM intervals with 15 min time-steps. On this basis, we propose a robust hourly economic bidding strategy model that determines the optimal energy bids in the RTM. We develop an adjustable robust counterpart of the model to address the RTM energy and flexiramp price uncertainties. The simulation results justify the efficacy of our proposed framework in gaining profits from the wholesale market.

24 POWER TRANSMISSION AND DISTRIBUTION↗