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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Rotated-Droop Control for Enhanced Stability and Power Decoupling in Microgrids With Complex Line Impedances

Classical droop control in microgrids predominantly assumes inductive line impedance, which simplifies implementation but causes power coupling and steady-state errors in systems with resistive and inductive lines. This paper proposes a rotated-droop control strategy for grid-forming inverters that reformulates the power equations by incorporating the magnitude and angle of the line impedance within a rotated reference frame. This method enhances the decoupling of active and reactive power dynamics without increasing complexity or requiring communication links. A small-signal state-space model was created to capture the dynamic behavior of the system under varying impedance parameters, preserving the original droop gains by rotating the power control structure. This allows eigenvalue-based stability analysis and enhances damping and transient performance. Simulation and experimental results validated the improved power-sharing performance, faster response, and robustness of the proposed method under different impedance conditions. This approach maintains the decentralized structure of the conventional droop control while enabling greater adaptability and scalability, making it suitable for modern inverter-based microgrids with dynamic topologies.

Campo-Ossa, Daniel Dario [Univ. of Puerto Rico, Ag↗
DOE OSTI2023

Blockchain for Fault-Tolerant Grid Operations

Radial topology and vast geographic coverage make distribution systems prone to widespread power outages upon the failure of a single (or multiple) upstream component. Fault-handling algorithms depend heavily on correct estimations of the system’s state to effectively isolate the affected area and reduce the number of affected customers while maintaining operational safety. The work described here leverages the core features of distributed, consensus-based decision-making processes and the immutability of blockchain, and demonstrates their value in improving fault-tolerant grid operations. In this work, blockchain was used to create a trusted data-sharing platform that enables independent actors to reconstruct the system state; this enables distributed resources to make intelligent decisions with limited knowledge. Although the process requires data sharing, its algorithms have been designed to limit the amount of private information that is exchanged, which helps preserve business-sensitive data and maintain customer privacy. In addition, by reducing the information that must be shared, the communication requirements are also reduced; (however, an in-depth analysis of the communication requirements is beyond the scope of this project). The proposed use cases are intended to represent a foundational basis for third parties to develop functional solutions that can eventually be deployed in the field. To further provide guidance, the envisioned use cases have incorporated design requirements that consider the blockchain characteristics and a need to limit information from surrounding resources, which preserve the assumption and the possibility that such resources could belong to different entities. This report presents a detailed design of the three use cases with the tools needed to enable the analysis being tested. The implemented gross error detection method can detect mismatches when the error exceeds 3.8 times the sensor’s rated accuracy. Detection of the circuit breaker state successfully identified the correct states across all simulation tests. A distribution-system power-flow solution in the simulator OpenDSS generally possesses a convergency tolerance of 0.01% on the voltage magnitude. The evaluation of possible reconnection using voltage magnitude—preserving the data ownership—has a voltage magnitude difference smaller than 0.001% from the OpenDSS result. The results preserving data ownership have a difference within the expected power flow tolerance with full knowledge of the system, which surpasses expectations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

The role of quantum computing in advancing scientific high-performance computing: A perspective from the ADAC institute

Quantum computing (QC) has gained significant attention over the past two decades due to its potential for speeding up classically demanding tasks. This transition from an academic focus to a thriving commercial sector is reflected in substantial global investments. While advancements in qubit counts and functionalities continue at a rapid pace, current quantum systems still lack the scalability for practical applications, facing challenges such as too high error rates and limited coherence times. Here, this perspective paper examines the relationship between QC and high-performance computing (HPC), highlighting their complementary roles in enhancing computational efficiency. It is widely acknowledged that even fully error-corrected QC will not be suited for all computational tasks. Rather, future compute infrastructures are anticipated to employ quantum acceleration within hybrid systems that integrate HPC and QC. While QC can enhance classical computing, traditional HPC remains essential for maximizing quantum acceleration. This integration is a priority for supercomputing centers and companies, sparking innovation to address the challenges of merging these technologies. The novelty of this work lies in its unique perspective, reflecting the collective insights of the Accelerated Data Analytics and Computing (ADAC) Institute, a global consortium of over 20 leading HPC centers. Recognizing the growing importance of QC, ADAC established a Quantum Computing Working Group in 2023 to foster collaboration and knowledge-sharing among its members. This paper synthesizes insights from the group’s collaborative efforts and incorporates findings from a member survey that captures shared experiences, ongoing projects, and strategic directions. By outlining the current landscape and challenges of QC integration into HPC ecosystems, this work offers HPC specialists practical and forward-looking guidance on the opportunities and implications of QC in computationally intensive endeavors.

Accelerated Data Analytics and↗
DOE OSTI2012

Human Reliability Analysis for Small Modular Reactors

Because no human reliability analysis (HRA) method was specifically developed for small modular reactors (SMRs), the application of any current HRA method to SMRs represents tradeoffs. A first- generation HRA method like THERP provides clearly defined activity types, but these activity types do not map to the human-system interface or concept of operations confronting SMR operators. A second- generation HRA method like ATHEANA is flexible enough to be used for SMR applications, but there is currently insufficient guidance for the analyst, requiring considerably more first-of-a-kind analyses and extensive SMR expertise in order to complete a quality HRA. Although no current HRA method is optimized to SMRs, it is possible to use existing HRA methods to identify errors, incorporate them as human failure events in the probabilistic risk assessment (PRA), and quantify them. In this paper, we provided preliminary guidance to assist the human reliability analyst and reviewer in understanding how to apply current HRA methods to the domain of SMRs. While it is possible to perform a satisfactory HRA using existing HRA methods, ultimately it is desirable to formally incorporate SMR considerations into the methods. This may require the development of new HRA methods. More practicably, existing methods need to be adapted to incorporate SMRs. Such adaptations may take the form of guidance on the complex mapping between conventional light water reactors and small modular reactors. While many behaviors and activities are shared between current plants and SMRs, the methods must adapt if they are to perform a valid and accurate analysis of plant personnel performance in SMRs.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2019

Determination of the Charge Materials Range in Multistage Charge Burden Optimization for Foundry Furnaces

Optimization of charge burden for foundry furnaces lies in determining a percentage or mass (kg, t) of the share of each charge material in the burden with the lowest unit cost. A classic task of charge burden optimization requires a definition of an objective function, which most often defines the cost of the charge burden and a system of constraints, including technological assumptions such as the balance of chemical elements for the required chemical composition of the charge or molten metal, limitations of the mass fraction of the individual elements of the charge, and others. The solution for such an optimization task is a set of starting values for the devices which weigh and proportion the charge materials for a foundry furnace. The consequences of deviations from proper values, causes by inaccurate weighing or proportioning and human error as well, can be limited by using an appropriately designed and implemented multistage optimization algorithm. This article presents a mathematical model of such an algorithm and discussion of its practical application. The algorithm as described below can be an important element of computer-aided decision to be made by employees in the process of batch compilation or automatically control devices dosing individual batch components. An IT system with an implemented algorithm may significantly increase the efficiency of charge preparation for a foundry furnace, guaranteeing its correct chemical composition despite batch materials dosing errors. It will contribute to a significant improvement of economic indicators of liquid metal production, with the effect of boosting the competitiveness of the foundry industry.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Planning for Variable Generation Integration through Balancing Authorities Consolidation

As more and more variable generation is integrated into power grids, many challenges and concerns arise for an individual balancing authority (BA) to balance the system with limited resources. Consolidating balancing authorities provides a promising method to mitigate these problems by enabling the sharing of resources through operating different BAs as a single BA. The diversity in load and renewable generation over a wide area can be effectively leveraged, which makes it possible to achieve significant savings in balancing requirements. This paper develops a detailed procedure to compute savings in load following and regulation service requirements due to BAs consolidation. It proposes several evaluation metrics for demonstrating the benefits of BA consolidation. Several study scenarios are designed for a set of BAs in the western United States to test the proposed procedure. Results have shown significant savings in the capacity, ramp rate, and energy of balancing service requirements. Important factors affecting the savings, such as forecast accuracy and cross correlation between forecast errors, are also discussed.

Diao, Ruisheng↗
DOE OSTI2025

HPC Campaign Management: Remote data access with user-defined error bound using ADIOS and ZFP

Remote access to large-scale scientific datasets, like those generated by combustion simulations or other high-performance computing (HPC) applications, presents a significant challenge. Downloading entire datasets is often impractical due to their size and the bandwidth limitations of typical networks. To address this challenge, we propose a novel approach that enables efficient remote access to large datasets distributed across multiple facilities. Our method enables technologies to download only the data values of a select variable, in a select region of interest, to a user-defined accuracy. For this purpose, we extended the ADIOS IO library to provide read functions with user-defined accuracy, a remote data server that understands multidimensional selections of specific variables, steps and accuracy from an ADIOS dataset, and which uses lossy compression on the remote site to reduce the data to be transferred back to the client. In addition, our extension of the ADIOS library collects metadata from multiple datasets in small files called Campaign Archives, which can be shared among project participants on any HPC, cloud or laptop, and which can easily facilitate the discovery of content and pointers to the data location as well as remote access to the data by local tools as if data was local. This feature called Campaign Management, enables a group of scientists to manage related datasets stored in multiple files, across multiple facilities as if it was in a single file/database. We demonstrate the effectiveness of our approach using a 1.5 TB dataset from the S3D combustion simulation on Frontier at the Oak Ridge Leadership Facility. Even a single variable from this dataset, at 64 GB, is too large to be processed on a standard laptop. We show two different reading patterns for 2D plots and 3D visualization, with careful settings that a scientist studying combustion data would do and show that running the same Python scripts on Frontier directly takes comparable time than running them on the local laptop with remote access to the data on Frontier.

Podhorszki, Norbert [ORNL] (ORCID:000000019647542X↗
DOE OSTI2021

Progress in Constraining Nuclear Symmetry Energy Using Neutron Star Observables Since GW170817

The density dependence of nuclear symmetry energy is among the most uncertain parts of the Equation of State (EOS) of dense neutron-rich nuclear matter. It is currently poorly known especially at suprasaturation densities partially because of our poor knowledge about isovector nuclear interactions at short distances. Because of its broad impacts on many interesting issues, pinning down the density dependence of nuclear symmetry energy has been a longstanding and shared goal of both astrophysics and nuclear physics. New observational data of neutron stars including their masses, radii, and tidal deformations since GW170817 have helped improve our knowledge about nuclear symmetry energy, especially at high densities. Based on various model analyses of these new data by many people in the nuclear astrophysics community, while our brief review might be incomplete and biased unintentionally, we learned in particular the following: (1) The slope parameter L of nuclear symmetry energy at saturation density ρ0 of nuclear matter from 24 new analyses of neutron star observables was about L≈57.7±19 MeV at a 68% confidence level, consistent with its fiducial value from surveys of over 50 earlier analyses of both terrestrial and astrophysical data within error bars. (2) The curvature Ksym of nuclear symmetry energy at ρ0 from 16 new analyses of neutron star observables was about Ksym≈−107±88 MeV at a 68% confidence level, in very good agreement with the systematics of earlier analyses. (3) The magnitude of nuclear symmetry energy at 2ρ0, i.e., Esym(2ρ0)≈51±13 MeV at a 68% confidence level, was extracted from nine new analyses of neutron star observables, consistent with the results from earlier analyses of heavy-ion reactions and the latest predictions of the state-of-the-art nuclear many-body theories. (4) While the available data from canonical neutron stars did not provide tight constraints on nuclear symmetry energy at densities above about 2ρ0, the lower radius boundary R2.01=12.2 km from NICER’s very recent observation of PSR J0740+6620 of mass 2.08±0.07M⊙ and radius R=12.2–16.3 km at a 68% confidence level set a tight lower limit for nuclear symmetry energy at densities above 2ρ0. (5) Bayesian inferences of nuclear symmetry energy using models encapsulating a first-order hadron–quark phase transition from observables of canonical neutron stars indicated that the phase transition shifted appreciably both L and Ksym to higher values, but with larger uncertainties compared to analyses assuming no such phase transition. (6) The high-density behavior of nuclear symmetry energy significantly affected the minimum frequency necessary to rotationally support GW190814’s secondary component of mass (2.50–2.67) M⊙ as the fastest and most massive pulsar discovered so far. Overall, thanks to the hard work of many people in the astrophysics and nuclear physics community, new data of neutron star observations since the discovery of GW170817 have significantly enriched our knowledge about the symmetry energy of dense neutron-rich nuclear matter.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Humboldt bay power plant decommissioning transition to civil works - 15039

Decommissioning of the Pacific Gas and Electric (PG and E) Company Humboldt Bay Power Plant (HBPP) Unit 3 nuclear facility has now, after more than three decades of SAFSTOR, completed the Plant Systems Removal Phase by removal of all radiologically significant plant systems from the buildings in June 2014. The HBPP historical design and construction, close proximity to the bay and associated tidal interactions poses unique challenges to an effective decommissioning effort as the Site transitions to a major earthwork project - designated as Civil Works. The last significant large component removal project remaining is segmentation and disposal of the reactor pressure vessel shell and this project is now integrated and executed under Civil Works with PG and E solely in an oversight role across the site beginning 2015. The value from run-up and mock-up testing of tooling to segment the HBPP reactor vessel will be discussed. Experience obtained, especially at error prone interfaces, during start-up, systemisation and operating phases for the First of a Kind (KOAK) tooling will be discussed. Implementation of the civil scope of work commenced July 2013. Its status and experience applicable to other decommissioning efforts will be provided from an owner's perspective. Implementation of the civil work scope includes development and implementation of oversight capability including policy, procedures and deployment of skilled, experienced and trained oversight staff in the field. Challenges encountered and solutions implemented during mobilization and ramp up of the civil contractor commensurate with demobilization of the self-perform staff will be covered. Partnering with the contractor to establish a good Client/Contractor relationship and tips on where to invest owner resources will be shared. Development of a solid baseline project schedule that incorporates regulatory constraints, client expectations and contract constraints and its importance to safe, compliant project execution will be shared. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Data-Informed Synthetic Networks of Water Distribution Systems for Resilience Analysis in Puerto Rico

The increasing potential of infrastructure disruptions calls for high-quality infrastructure models to be used in resilience analysis and decision making. Unfortunately, many utilities and communities do not have access to accurate and detailed models due to a lack of data and resources. Furthermore, security restrictions on sharing infrastructure models present roadblocks to research, analysis, and decision making. Recent advances in the development of synthetic water distribution models provide a potential solution to this problem. There is an opportunity to improve these methods by leveraging incomplete pipe datasets to aid synthetic network generation. To address this gap, we developed a methodology for synthetic network generation that incorporates partial pipe data using a modification of the minimum cost flow algorithm for network generation and pipe sizing. This methodology demonstrates how partial pipe data can be leveraged to improve site-specific synthetic network generation. For the study area of Mayagüez, Puerto Rico, a synthetic model generated using 50% of real pipe data matches the pressure of the validation system with an average error of 23.5 m of head, which improves upon the average error of 31.6 m of head produced by a synthetic model generated using no data of the real pipes. Additionally, synthetic networks are shown to replicate the pressure response under a disruption scenario of the validation network, suggesting potential use in resilience analysis.

resilience analysis↗
DOE OSTI2019

A Low Power, High Speed Readout for Pixel Detectors Based on an Arbitration Tree

A low-power, high-speed arbitration tree for pixel detector readout is presented. The synchronized, binary tree priority encoder establishes a position dependent priority list at the start of every time frame. Pixels that indicate the presence of data for readout, are sequentially granted access to a shared bus for data transfer to the periphery, without the use of an additional global strobe signal. It can be used for either full frame imaging or zero-suppressed readout, in which case it can simultaneously generate the pixel address. To increase the readout frame rate, the pixel array is subdivided into two halves, which allows interleaved latching of data at the output serializer. The design was implemented in a 65 nm LP-CMOS process for the readout of a 64 x 64 pixel array. Measurement results demonstrate a deadtime-less, full frame imaging rate of ~50 kfps, achieved with a dedicated output for every (32 x 32) 1024 pixels and for a pixel data packet of 11 bits, with no bit errors detected over 1000 frames. The measured energy per bit is 0.94 pJ.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Myths of German Graphite in World War II, with Original Translations

We re-examine the common narrative that a 1941 experimental error by physicists Walther Bothe and Peter Jensen led Germany to abandon graphite as a reactor moderator during World War II. We first detail the history of both German and American graphite experiments, noting that the Americans faced similar setbacks but succeeded only at the end of a costly 18-month graphite purification program. We then use Monte Carlo N-Particle simulations to reconstruct Bothe's 1941 experiment. We find the thermal absorption cross section of Bothe's Siemens electrographite to be 12.2 mb, in contrast to his reported 7.9 mb. This discrepancy arises because the neutrons in Bothe's experiment did not reach thermal equilibrium, leading to an underestimation of neutron absorption. Additionally, despite misconceptions that the Germans were unaware of boron impurities, we share evidence that Wilhelm Hanle accurately measured boron and cadmium impurities in the electrographite. To support our findings, we provide 9 excerpted and 3 complete English translations of classified wartime reports by Heisenberg, Joos, Bothe, Jensen, Höcker, Hanle, and Kremer. Our work aims to illuminate the rational constraints behind Germany's decision to forgo graphite moderation.

Park, Patrick J.↗
DOE OSTI2012

Target Strength of Southern Resident Killer Whales (Orcinus orca): Measurement and Modeling

A major criterion for tidal power licensing in Washington’s Puget Sound is the management of the risk of injury to killer whales due to collision with moving turbine blades. An active monitoring system is being proposed for killer whale detection, tracking, and alerting that links to and triggers temporary turbine shutdown when there is risk of collision. Target strength (TS) modeling of the killer whale is critical to the design and application of any active monitoring system. A 1996 study performed a high-resolution measurement of acoustic reflectivity as a function of frequency of a female bottlenose dolphin (2.2 m length) at broadside aspect and TS as a function of incident angle at 67 kHz frequency. Assuming that killer whales share similar morphology structure with the bottlenose dolphin, we extrapolated the TS of an adult killer whale 7.5 m in length at 67 kHz frequency with -8 dB at broadside aspect and -28 dB at tail side. The backscattering data from three Southern Resident killer whales were analyzed to obtain the TS measurement. These data were collected at Lime Kiln State Park using a split-beam system deployed from a boat. The TS of the killer whale at higher frequency (200 kHz) was estimated based on a three-layer model for plane wave reflection from the lung of the whale. The TS data of killer whales were in good agreement with our model. In this paper, we also discuss and explain possible causes for measurement estimation error.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

NLR HPC Eagle GPU Node Metrics

Ganglia node metrics and iLO (Integrated Lights Out) power data captured from six representative Eagle GPU nodes The Eagle HPC operated at NLR from 2019 through 2024. Eagle was a 2,000-node, 8-petaflop system. This dataset is a representative sample of metrics for 6 of the GPU nodes. Each GPU node contained 2 CPUs and 2 GPUs. Data provided in compressed CSV format. Ganglia and iLO Power Time Series Fields ts: Timestamp dv: Device / Node - Rack and Unit - r103u17 == r(ack)103u(nit)17 mt: Metric (only present for Ganglia) vl: Value - Value in watts for iLO power (instantaneous value at sampling time) or specified Ganglia metric below Ganglia Metrics Metric name -- Metric description -- Unit cpu_aidle -- Percent of time since boot idle CPU -- Percent cpu_idle -- Percent CPU idle -- Percent cpu_nice -- Percent CPU nice -- Percent cpu_speed -- Speed in MHz of CPU -- MHz cpu_user -- Percent CPU user -- Percent cpu_wio -- The percentage of CPU Wait I/O -- Percent gpu0_bar1_memory -- Used GPU bar1 memory -- MB gpu0_decoder_util -- GPU decoder utilization -- Percent gpu0_ecc_db_error -- Total ECC error counts for the GPU -- Number gpu0_encoder_util -- GPU encoder utilization -- Percent gpu0_fan -- Fan speed -- RPM gpu0_fb_memory -- Used GPU framebuffer memory -- MB gpu0_graphics_clock_report -- Current clock speeds for the device -- MHz gpu0_mem_total -- Memory total -- MB gpu0_mem_util -- Memory utilization -- Percent gpu0_power_usage_report -- Power usage report -- Watts gpu0_temp -- GPU 1 temperature -- Celsius gpu1_bar1_memory -- Used GPU bar1 memory -- MB gpu1_decoder_util -- GPU decoder utilization -- Percent gpu1_ecc_db_error -- Total ECC error counts for the GPU -- Number gpu1_encoder_util -- GPU encoder utilization -- Percent gpu1_fan -- Fan speed -- RPM gpu1_fb_memory -- Used GPU framebuffer memory -- MB gpu1_graphics_clock_report -- Current clock speeds for the GPU -- MHz gpu1_mem_total -- Memory total -- MB gpu1_mem_util -- Memory utilization -- MB gpu1_power_usage_report -- Power usage report -- Watts gpu1_temp -- GPU 1 temperature -- Celsius ipmi_cpu1_temp -- CPU 1 temperature -- Celsius ipmi_cpu2_temp -- CPU 2 temperature -- Celsius ipmi_inlet_ambient_temp -- Temperature measured at intake -- Celsius ipmi_vr_p1_temp -- CPU 1 voltage regulator temperature -- Celsius ipmi_vr_p2_temp -- CPU 2 voltage regulator temperature -- Celsius mem_buffers -- Amount of buffered memory -- Bytes mem_cached -- Amount of cached memory -- Bytes mem_free -- Amount of available memory -- Bytes mem_shared -- Amount of shared memory -- Bytes mem_total -- Amount of available memory -- Bytes

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Model of Procedure Usage – Results from a Qualitative Study to Inform Design of Computer-Based Procedures

The nuclear industry is constantly trying to find ways to decrease the human error rate, especially the human errors associated with procedure use. As a step toward the goal of improving procedure use performance, researchers, together with the nuclear industry, have been looking at replacing the current paper-based procedures with computer-based procedure systems. The concept of computer-based procedures is not new by any means; however most research has focused on procedures used in the main control room. Procedures reviewed in these efforts are mainly emergency operating procedures and normal operating procedures. Based on lessons learned for these previous efforts we are now exploring a more unknown application for computer based procedures - field procedures, i.e. procedures used by nuclear equipment operators and maintenance technicians. The Idaho National Laboratory, the Institute for Energy Technology, and participants from the U.S. commercial nuclear industry are collaborating in an applied research effort with the objective of developing requirements and specifications for a computer-based procedure system to be used by field operators. The goal is to identify the types of human errors that can be mitigated by using computer-based procedures and how to best design the computer-based procedures to do this. The underlying philosophy in the research effort is “Stop – Start – Continue”, i.e. what features from the use of paper-based procedures should we not incorporate (Stop), what should we keep (Continue), and what new features or work processes should be added (Start). One step in identifying the Stop – Start – Continue was to conduct a baseline study where affordances related to the current usage of paper-based procedures were identified. The purpose of the study was to develop a model of paper based procedure use which will help to identify desirable features for computer based procedure prototypes. Affordances such as note taking, markups, sharing procedures between fellow coworkers, the use of multiple procedures at once, etc. were considered. The model describes which affordances associated with paper based procedures should be transferred to computer-based procedures as well as what features should not be incorporated. The model also provides a means to identify what new features not present in paper based procedures need to be added to the computer-based procedures to further enhance performance. The next step is to use the requirements and specifications to develop concepts and prototypes of computer-based procedures. User tests and other data collection efforts will be conducted to ensure that the real issues with field procedures and their usage are being addressed and solved in the best manner possible. This paper describes the baseline study, the construction of the model of procedure use, and the requirements and specifications for computer-based procedures that were developed based on the model. It also addresses how the model and the insights gained from it were used to develop concepts and prototypes for computer based procedures.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Biomimetic model-based advanced control strategy integrated with multi-agent optimization for nonlinear chemical processes

Here, a novel framework is proposed for integrating biomimetic-based advanced control and multi-agent optimization approaches for nonlinear chemical process applications. In particular, a Biologically-Inspired Optimal Control Strategy, denoted as BIO-CS, is combined with multi-agent optimization (MAO) techniques to provide optimal solutions for dynamic systems. In this combined framework, the BIO-CS algorithm employs gradient-based optimal control solvers for the intermediate problems associated with the leader-follower agents’ local interactions. Also, the MAO uses the capabilities of heuristic-based optimization techniques by sharing process information to obtain optimal operating setpoints for the controller considering an overall process objective. The applicability of the proposed method is demonstrated using a nonlinear, multivariable, process model of a fermentation system. Specifically, the optimal operating points are computed by the MAO implementation for setpoint tracking, trajectory tracking and plant-model mismatch scenarios for BIO-CS application. Results of the developed framework are compared to a gradient-based Sequential Quadratic Programming (SQP) technique and a classical proportional-integral (PI) controller in terms of optimization and control studies, respectively. As an additional contribution, BIO-CS is also cast as a model predictive controller (MPC) for the first time and compared to the agent-based BIO-CS approach in terms of computational time and tracking error. Closed-loop control results show up to 46% improvement in tracking performance during transient for the multi-agent BIO-CS when compared to BIO-CS as MPC for additional computational expense. The obtained results illustrate the capabilities of this novel integrated framework including BIO-CS as MPC to achieve desired nonlinear system performance for various scenarios.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Day-ahead photovoltaic power production forecasting methodology based on machine learning and statistical post-processing

A main challenge towards ensuring large-scale and seamless integration of photovoltaic systems is to improve the accuracy of energy yield forecasts, especially in grid areas of high photovoltaic shares. The scope of this paper is to address this issue by presenting a unified methodology for hourly-averaged day-ahead photovoltaic power forecasts with improved accuracy, based on data-driven machine learning techniques and statistical post-processing. More specifically, the proposed forecasting methodology framework comprised of a data quality stage, data-driven power output machine learning model development (artificial neural networks), weather clustering assessment (K-means clustering), post-processing output optimisation (linear regressive correction method) and the final performance accuracy evaluation. The results showed that the application of linear regression coefficients to the forecasted outputs of the developed day-ahead photovoltaic power production neural network improved the performance accuracy by further correcting solar irradiance forecasting biases. The resulting optimised model provided a mean absolute percentage error of 4.7% when applied to historical system datasets. Finally, the model was validated both, at a hot as well as a cold semi-arid climatic location, and the obtained results demonstrated close agreement by yielding forecasting accuracies of mean absolute percentage error of 4.7% and 6.3%, respectively. Finally, the validation analysis provides evidence that the proposed model exhibits high performance in both forecasting accuracy and stability.

42 ENGINEERING↗
DOE OSTI2019

Counting Kmers for Biological Sequences at Large Scale

Counting the abundance of all the distinct kmers in biological sequence data is a fundamental step in bioinformatics. These applications include de novo genome assembly, error correction, etc. With the development of sequencing technology, the sequence data in a single project can reach Petabyte-scale or Terabyte-scale nucleotides. Counting demand for the abundance of these sequencing data is beyond the memory and computing capacity of single computing node, and how to process it efficiently is a challenge on a high-performance computing cluster. As such, we propose SWAPCounter, a highly scalable distributed approach for kmer counting. This approach is embedded with an MPI streaming I/O module for loading huge data set at high speed, and a counting bloom filter module for both memory and communication efficiency. By overlapping all the counting steps, SWAPCounter achieves high scalability with high parallel efficiency. In this work, the experimental results indicate that SWAPCounter has competitive performance with two other tools on shared memory environment, KMC 2 , and MSPKmerCounter. Moreover, SWAPCounter also shows the highest scalability under strong scaling experiments. In our experiment on Cetus supercomputer, SWAPCounter scales to 32,768 cores with 79% parallel efficiency (using 2048 cores as baseline) when processing 4 TB sequence data of 1000 Genomes. The source code of SWAPCounter is publicly available at https://github.com/mengjintao/SWAPCounter.

59 BASIC BIOLOGICAL SCIENCES↗