SEARCH · Engineering Papers

Results for “Dynamic Programming”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,351 records · Page 75

All sources NASA NTRS DOE OSTI

DOE OSTI2021

Two-stage dynamic deregulation of metabolism improves process robustness & scalability in engineered E. coli.

Here, we report that two-stage dynamic control improves bioprocess robustness as a result of the dynamic deregulation of central metabolism. Dynamic control is implemented during stationary phase using combinations of CRISPR interference and controlled proteolysis to reduce levels of central metabolic enzymes. Reducing the levels of key enzymes alters metabolite pools resulting in deregulation of the metabolic network. Deregulated networks are less sensitive to environmental conditions improving process robustness. Process robustness in turn leads to predictable scalability, minimizing the need for traditional process optimization. We validate process robustness and scalability of strains and bioprocesses synthesizing the important industrial chemicals alanine, citramalate and xylitol. Predictive high throughput approaches that translate to larger scales are critical for metabolic engineering programs to truly take advantage of the rapidly increasing throughput and decreasing costs of synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Flexible dynamic boundary microgrid operation considering network and load unbalances

Flexible microgrids with dynamic boundaries have recently been introduced in the literature. With the ability to reconfigure the topology of the microgrids dynamically through remotely controlled switches, flexible microgrids with dynamic boundaries can further improve the resiliency and energy efficiency of microgrids with distributed energy resources (DERs). This paper focuses on the optimal operation considering one of the predominant characteristics of microgrids and distribution systems – unbalanced networks and loads. In existing literature, balanced modeling of microgrids is more common due to its attractive simplicity. The three-phase power unbalance has not been considered as a constraint on the generation units in a microgrid. Further, negative sequence constraints have also been neglected. In this article, we propose a set of constraints that is specifically related to the capabilities of inverter interfaced resources to supply unbalanced current/power when the microgrid is islanded from the main distribution grid. We incorporate the new set of constraints into two optimization formulations leveraging two convex relaxations of the three-phase power flow equations: mixed-integer linear programming (MILP) and mixed-integer semidefinite programming (MISDP) that optimize the dispatch of controllable switches and DERs in the microgrid. The algorithms are then extended to networked microgrids with grid-forming sources. We test the algorithms on a realistic community microgrid model in Puerto Rico as well as standardized IEEE distribution test feeders. The testing results demonstrate the performance of the proposed algorithms. The MILP is fast and scalable, and the MISDP enforces the negative sequence voltage constraints.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2019

Challenges in simulating beam dynamics of dielectric laser acceleration

Dielectric Laser Acceleration (DLA) achieves the highest gradients among structure-based electron accelerators. The use of dielectrics increases the breakdown field limit, and thus the achievable gradient, by a factor of at least 10 in comparison to metals. Experimental demonstrations of DLA in 2013 led to the Accelerator on a Chip International Program (ACHIP), funded by the Gordon and Betty Moore Foundation. In ACHIP, our main goal is to build an accelerator on a silicon chip, which can accelerate electrons from below 100 keV to above 1 MeV with a gradient of at least 100 MeV/m. For stable acceleration on the chip, magnet-only focusing techniques are insufficient to compensate the strong acceleration defocusing. Thus, spatial harmonic and Alternating Phase Focusing (APF) laser-based focusing techniques have been developed. Additionally, we have developed the simplified symplectic tracking code DLAtrack6D, which makes use of the periodicity and applies only one kick per DLA cell, which is calculated by the Fourier coefficient of the synchronous spatial harmonic. Due to coupling, the Fourier coefficients of neighboring cells are not entirely independent and a field flatness optimization (similarly as in multi-cell cavities) needs to be performed. The simulation of the entire accelerator on a chip by a Particle In Cell (PIC) code is possible, but impractical for optimization purposes. Finally, we have also outlined the treatment of wake field effects in attosecond bunches in the grating within DLAtrack6D, where the wake function is computed by an external solver.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

SymbolNet: neural symbolic regression with adaptive dynamic pruning for compression

Abstract Compact symbolic expressions have been shown to be more efficient than neural network (NN) models in terms of resource consumption and inference speed when implemented on custom hardware such as field-programmable gate arrays (FPGAs), while maintaining comparable accuracy (Tsoi et al 2024 EPJ Web Conf. 295 09036). These capabilities are highly valuable in environments with stringent computational resource constraints, such as high-energy physics experiments at the CERN Large Hadron Collider. However, finding compact expressions for high-dimensional datasets remains challenging due to the inherent limitations of genetic programming (GP), the search algorithm of most symbolic regression (SR) methods. Contrary to GP, the NN approach to SR offers scalability to high-dimensional inputs and leverages gradient methods for faster equation searching. Common ways of constraining expression complexity often involve multistage pruning with fine-tuning, which can result in significant performance loss. In this work, we propose S y m b o l N e t , a NN approach to SR specifically designed as a model compression technique, aimed at enabling low-latency inference for high-dimensional inputs on custom hardware such as FPGAs. This framework allows dynamic pruning of model weights, input features, and mathematical operators in a single training process, where both training loss and expression complexity are optimized simultaneously. We introduce a sparsity regularization term for each pruning type, which can adaptively adjust its strength, leading to convergence at a target sparsity ratio. Unlike most existing SR methods that struggle with datasets containing more than O ( 10 ) inputs, we demonstrate the effectiveness of our model on the LHC jet tagging task (16 inputs), MNIST (784 inputs), and SVHN (3072 inputs).

Tsoi, Ho Fung (ORCID:0000000225502184)↗

DOE OSTI2015

Probing Complexity using the Linac Coherent Light Source (LCLS) and the Advanced Light Source (ALS)

The goal of our research program is to investigate fundamental interactions between photons and molecular/nano-systems to advance our quantitative understanding of electron correlations, charge transfer and many body phenomena. Our research projects focus on probing, on a femtosecond time-scale, multi-electron interactions and tracing nuclear motion in order to understand, and ultimately control energy flow and charge transfer processes from electromagnetic radiation to matter. The experiments will be carried out with state of the art instrumentation built by the P.I. team with funds from a DoE "Single Investigator and Small Group Research" (SISGR) grant. The research projects carried out the past three years consisted of first experiments using the Linac Coherent Light Source (LCLS) x-ray free electron laser (FEL) facility at the SLAC National Laboratory, as well as the study of correlated processes in select anions using the Advanced Light Source (ALS). A report for the past cycle is described in section II. These studies have paved the way for our renewal application for the next three years. Our research interests for the next three years extend our past and present research by carrying out time-resolved measurements described in section III. They will consist of: a) The study of molecular dynamics that happen on ultrafast time scales, using pump-probe schemes and the study of non-linear physics in the x-ray regime via multi-photon absorption from the LCLS. This will be achieved by measuring and examining both electronic and nuclear dynamics subsequent to the interaction of molecules and nano-systems with LCLS pulses of various wavelength, intensity and pulse duration as described in section III.A. b) The study of molecular dynamics and correlated processes via absorption of vuv-soft x-rays from the Advanced Light Source (ALS) at Lawrence Berkeley Laboratory to provide single-photon ionization baseline results for LCLS studies. In addition, we will study the photodetachment of anions using the ALS as described in section III. B. The PI has an ALS approved program (AP) thus has guaranteed beamtime. Our research underpins several aspects of the DOE mission since our investigations of the formation and evolution of energized states in molecules and nanostructures provides a fundamental basis for understanding elementary processes in solar energy conversion and radiation-induced chemistry. Most of our work is carried out in a strong partnership with theorists. Our proposed work falls in the class of research reported to be timely and necessary by the 2013 DoE Basic Energy Sciences Advisory Committee (BESAC) Subcommittee report on Future X-ray Light Sources. Specifically, our proposed experiments fall in the category labeled class II, “Spectroscopy and Dynamics with FELs”.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2023

Reinforcement Learning for Load-balanced Parallel Particle Tracing

We explore an online reinforcement learning (RL) paradigm to dynamically optimize parallel particle tracing performance in distributed-memory systems. Our method combines three novel components: (1) a work donation algorithm, (2) a high-order workload estimation model, and (3) a communication cost model. First, we design an RL-based work donation algorithm. Our algorithm monitors workloads of processes and creates RL agents to donate data blocks and particles from high-workload processes to low-workload processes to minimize program execution time. The agents learn the donation strategy on the fly based on reward and cost functions designed to consider processes' workload changes and data transfer costs of donation actions. Second, we propose a workload estimation model, helping RL agents estimate the workload distribution of processes in future computations. Third, we design a communication cost model that considers both block and particle data exchange costs, helping RL agents make effective decisions with minimized communication costs. We demonstrate that our algorithm adapts to different flow behaviors in large-scale fluid dynamics, ocean, and weather simulation data. Our algorithm improves parallel particle tracing performance in terms of parallel efficiency, load balance, and costs of I/O and communication for evaluations with up to 16,384 processors.

Distributed and parallel particle tracing↗

DOE OSTI2013

Advanced Natural Gas Reciprocating Engine(s)

Energy independence and fuel savings are hallmarks of the nation’s energy strategy. The advancement of natural gas reciprocating engine power generation technology is critical to the nation’s future. A new engine platform that meets the efficiency, emissions, fuel flexibility, cost and reliability/maintainability targets will enable American manufacturers to have highly competitive products that provide substantial environmental and economic benefits in the US and in international markets. Along with Cummins and Waukesha, Caterpillar participated in a multiyear cooperative agreement with the Department of Energy to create a 50% efficiency natural gas powered reciprocating engine system with a 95% reduction in NOx emissions by the year 2013. This platform developed under this agreement will be a significant contributor to the US energy strategy and will enable gas engine technology to remain a highly competitive choice, meeting customer cost of electricity targets, and regulatory environmental standard. Engine development under the Advanced Reciprocating Engine System (ARES) program was divided into phases, with the ultimate goal being approached in a series of incremental steps. This incremental approach would promote the commercialization of ARES technologies as soon as they emerged from development and would provide a technical and commercial foundation of later-developing technologies. Demonstrations of the Phase I and Phase II technology were completed in 2004 and 2008, respectively. Program tasks in Phase III included component and system development and testing from 2009-2012. Two advanced ignition technology evaluations were investigated under the ARES program: laser ignition and distributed ignition (DIGN). In collaboration with Colorado State University (CSU), a laser ignition system was developed to provide ignition at lean burn and high boost conditions. Much work has been performed in Caterpillar’s DIGN program under the ARES program. This work has consisted of both modeling and single cylinder engine experiments to quantify DIGN performance. The air handling systems of natural gas engines dissipate a percentage of available energy as a result of both flow losses and turbomachinery inefficiencies. An analytical study was initiated to increase compressor efficiency by employing a 2-stage inter-cooled compressor. Caterpillar also studied a turbo-compound system that employs a power turbine to recover energy from the exhaust gases for improved engine efficiency. Several other component and system investigations were undertaken during the final phase of the program to reach the ultimate ARES goals. An intake valve actuation system was developed and tested to improve engine efficiency, durability and load acceptance. Analytical modeling and materials testing were performed to evaluate the performance of steel pistons and compacted graphite iron cylinder head. Effort was made to improve the detonation sensing system by studying and comparing the performance of different pressure sensors. To reduce unburned hydrocarbon emissions, different camshafts were designed and built to investigate the effect of exhaust valve opening timing and value overlap. 1-D & 3-D coupled simulation was used to study intake and exhaust manifold dynamics with the goal of reducing load in-balance between cylinders. Selective catalytic reduction with on-board reductant generation to reduce NOx emissions was also engine tested. An effective mean to successfully deploy ARES technologies into the energy markets is to deploy demonstration projects in the field. In 2010, NETL and Caterpillar agreed to include a new “opportunity fuel” deliverable and two field demonstrations in the ARES program. An Organic Rankine Cycle system was designed with production intent incorporating lessons learned from the Phase II demonstration. Unfortunately, business conditions caused Caterpillar to cancel this demonstration in 2011. Nonetheless, Caterpillar partnered with a local dealer to deploy an ARES class engine using syngas from a biomass gasifier as the DE-FC26-01CH11079 primary combustion fuel in Gleason, TN. Upon the successful start-up and commissioning of the demonstration unit, ownership of the system was transferred to the dealer. In order to further our understanding of syngas combustion, a fundamental combustion study on syngas combustion at high pressure and lean condition was conducted through the collaboration with University of Southern California. A Methane program was also developed to rate engine performance for various compositions of syngas using empirical data obtained at CSU. While much work remains in terms of extending and integrating these developments into commercial products, it is evident that engine manufacturers on our own or through private consortium efforts could not have overcome the financial hurdles to drive these improvements into reciprocating engine and system capabilities, helping maintain the natural gas reciprocating engine power generation technology as a strong option for electric power markets, both in the United States and worldwide.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2017

Factors Influencing Energy Use and Carbon Emissions in China

This research project was designed to fill a critical void in our understanding of the state of energy research and innovation in China. It seeks to provide a comprehensive review and accounting of the various elements of the Chinese government and non-governmental sectors (commercial, university, research institutes) that are engaged in energy-related R&D and various aspects of energy innovation, including specific programs and projects designed to promote renewable energy innovation and energy conservation. The project provides an interrelated descriptive, statistical, and econometric account of China's overall energy innovation activities and capabilities, spanning the full economy with a particular focus on the dynamic industrial sector.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2018

9 th American Conference on Neutron Scattering (ACNS 2018)

The 9th American Conference on Neutron Scattering (ACNS) was held June 24-28, 2018 in College Park, Maryland. The meeting was coordinated by the Neutron Scattering Society of America (NSSA) and attracted 335 registered attendees. The meeting was chaired by NSSA vice president Patrick Woodward (The Ohio State University) assisted by NSSA president Despina Louca (University of Virginia, NSSA secretary Katherine Page (Oak Ridge National Laboratory), and local organizing chairs Rob Briber (University of Maryland) and Peter Gehring (NIST Gaithersburg). As in past years, the Materials Research Society assisted with planning, logistics and operation of the conference. The meeting schedule consisted of a morning common session featuring a lecture by a scientist receiving an award from the NSSA and a plenary lecture. The remainder of the scientific program consisted of four parallel sessions featuring invited and contributed talks together with poster sessions in the afternoon / evening. The science program was coordinated by program co-chairs Efrain Rodriguez (University of Maryland) and Matt Helgeson (University of California Santa Barbara) and was divided into the following research areas: (a) Advances in Neutron Methods; (b) Hard Condensed Matter; (c) Soft Matter; (d) Biological Structures and Dynamics; (e) Neutrons for Energy and Sustainability; (f) Materials Chemistry and Synthesis; (g) Structural Materials and Engineering; and (h) Neutron Physics.

36 MATERIALS SCIENCE↗

DOE OSTI2014

Electron-Ion Collider - Plans for Realization

Understanding the emergence of nucleons and nuclei and their interactions from the properties and dynamics of quarks and gluons in Quantum Chromo-Dynamics (QCD) is a fundamental and compelling goal of nuclear science. An Electron-Ion Collider (EIC) was designated in the 2007 Nuclear Physics Long Range Plan as "embodying the vision for reaching the next QCD frontier," extending the QCD science programs in the U.S. established at both the CEBAF accelerator at JLab and RHIC at BNL in dramatic and fundamentally important ways. The 2013 Report of the NSAC Subcommittee on Major Nuclear Physics Facilities for the Next Decade reaffirmed an EIC as "absolutely central in its ability to contribute to world-leading science in the next decade." Two proposals for the EIC are being considered in the U.S.: one each at BNL and at Jefferson Laboratory. In this presentation we will review these proposals of the EIC, their implementation plan, and comment on the physics opportunities they present to the nuclear science communities in the next decade

Rossi, Patrizia↗

DOE OSTI2024

Percheron Power Archimedes Screw Turbine Analysis (Abstract)

The development of the Percheron Power (Percheron) composite Archimedes screw turbine (AST) is based upon employing newly developed theoretical mathematical models for optimizing the water volume carried through the AST for a given diameter, combined with minimizing efficiency losses due to bypass flow and friction. The key feasibility issues associated with producing the composite blades will be to understand the strength, fatigue, and wear performance of the AST blades and associated components, and how these factors change along the length of the turbine. To get to this understanding of material property requirements, Percheron needs free-surface computational fluid dynamics (CFD) models of the AST designs and to perform interactive modeling between the turbine blade optimization and component design based on finite element method stress analysis (FEA). The workscope and analyses requested by Percheron in the Small Business Voucher (SBV) program are well aligned with PNNL capability and recent work experience in performing CFD and FEA analysis for hydropower and marine energy turbines. The CFD analysis will provide estimates of power, efficiency, and surface forces on the blades. The forces on the blade will be transferred to the FEA analysis that will be used to evaluate the material stresses. The CFD and FEA analyses will be repeated for different AST designs provided to PNNL by Percheron. The work conducted in this SBV project will complement the existing Percheron FOA project by providing better defined parameters for design and material selection for the turbine unit prior to manufacture of initial test units.

42 ENGINEERING↗

DOE OSTI2025

Advanced Transmission Technologies (ATTs) Supplier Cohort Workshops Cohort Summary [Slides]

This Summary slide deck summarizes the key outcomes of the Advanced Transmission Technologies (ATTs) supplier cohort, part of Idaho National Laboratory’s (INL) Technical Assistance for Digital Assurance (TADA) program. The program aimed to strengthen grid resilience through cybersecurity controls, supply-chain security, and Cyber-Informed Engineering (CIE) for advanced transmission technologies. The cohort brought together vendors representing the full range of Grid-Enhancing Technologies (GETs), including providers of Dynamic Line Ratings (DLR), Advanced Power Flow Control (APFC), Transmission Topology Optimization (TTO), and High-Performance Conductors (HPCs). Discussions focused on institutional, integration, and operational barriers limiting GET adoption; cybersecurity risks at EMS/SCADA, cloud, and network integration points; and supply-chain transparency issues such as semiconductor dependence and SBOM/HBOM expectations. Participants also addressed operator trust, human-in-the-loop requirements, and challenges with utility adoption, while exploring how CIE can support secure deployment of GETs. This deck represents a consolidated summary of challenges and risks identified by vendors, cross-cutting themes and technology-specific insights from three cohort workshops, and actionable mitigations to guide utilities, vendors, and the Department of Energy in advancing secure, trusted deployment of GETs.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2019

Quantum Mechanical Modeling of the Vibrational Spectra of Minerals with a Focus on Clays

We present an overview of how to use quantum mechanical calculations to predict vibrational frequencies of molecules and materials such as clays and silicates. Other methods of estimating vibrational frequencies are mentioned, such as classical molecular dynamics simulations; references are given for additional information on these approaches. Herein, we discuss basic vibrational theory, calculating Raman and infrared intensities, steps for creating realistic models, and applications to spectroscopy, thermodynamics, and isotopic fractionation. There are a wide variety of programs and methods that can be employed to model vibrational spectra, but this work focuses on hybrid density functional theory (DFT) approaches. Many of the principles are the same when used in other programs and DFT methods, so a novice can benefit from simple examples that illustrate key points to consider when modeling vibrational spectra. Other methods and programs are listed to give the beginner a starting point for exploring and choosing which approach will be best for a given problem. The modeler should also be aware of the numerous analytical methods available for obtaining information on vibrations of atoms in molecules and materials. In addition to traditional infrared and Raman spectroscopy, sum-frequency generation (SFG) and inelastic neutron scattering (INS) are also excellent techniques for obtaining vibrational frequency information in certain circumstances.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

Hydrodynamic Analysis and Optimization of Aquantis Marine Turbine: Cooperative Research and Development (Final Report)

The primary aim of this proposal is to improve the accurate prediction of hydrodynamic performance and dynamic load responses of the AQ10 floating axial-flow tidal turbine with a tri-cat mooring configuration. The validation of reduced-order modeling approaches with high-fidelity model will be implemented. Additionally, the frequency response domain, Response Amplitude Floating Wind (RAFT) toolbox plus an optimizer expanded for marine hydrokinetic turbines under the Submarine Hydrokinetic And Riverine Kilo-megawatt. Systems (SHARKS) program will be used for designing and exploring different key design parameters (platform dimension, mooring layout and its parameters) of next marine hydrokinetic (MHK) turbine generation.

16 TIDAL AND WAVE POWER↗

DOE OSTI2020

Compiler and Runtime Approaches to Enable Large-Scale Irregular Programs. Final report, July 2013 - July 2019

While regular algorithms, characterized by operations on dense matrices and arrays, have long been the mainstay of scientific, high-performance computing, irregular algorithms, which feature unpredictable accesses to pointer-based data structures, are becoming increasingly common in high performance computing, arising in graph analysis, data mining and visualization, among other domains. Unfortunately, the defining characteristics of irregular applications, their dynamic, unpredictable, data-dependent access patterns and data layouts, make achieving high performance on large scale systems difficult. Scaling applications to peta- and exa-scale requires carefully controlling communication and data movement and placement, an inherently difficult task when access patterns and data layouts are unpredictable! Most irregular applications that attain high performance must be painstakingly hand-written and hand-tuned, with few common principles or paradigms uniting various implementations and easing future development. Despite the increasing importance of irregular applications, there is little programmer knowledge, and even less compiler ability, devoted to optimizing them. This project aims to solve these problems. By allowing programmers to write irregular applications in high level forms, with at most a few annotations highlighting key structural properties, programmers can focus on developing their algorithms and methods. The compiler and run-time system can take on the tedious task of optimizing the application for execution at large scales, and can automatically provide efficient implementations. This will provide portability and ease maintenance for existing irregular applications, but, more importantly, open up whole new domains of computational science to large-scale, high-performance simulation codes.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Benthic storms, nepheloid layers, and linkage with upper ocean dynamics in the western North Atlantic

Benthic storms are episodic periods of strong abyssal currents and intense, benthic nepheloid (turbid) layer development. In order to interpret the driving forces that create and sustain these storms, we synthesize measurements of deep ocean currents, nephelometer-based particulate matter (PM) concentrations, and seafloor time-series photographs collected during several science programs that spanned two decades in the western North Atlantic. Benthic storms occurred in areas with high sea-surface eddy kinetic energy, and they most frequently occurred beneath the meandering Gulf Stream or its associated rings, which generate deep cyclones, anticyclones, and/or topographic waves; these create currents with sufficient bed-shear stress to erode and resuspend sediment, thus initiating or enhancing benthic storms. Occasionally, strong currents do not correspond with large increases in PM concentrations, suggesting that easily erodible sediment was previously swept away. Periods of moderate to low currents associated with high PM concentrations are also observed; these are interpreted as advection of PM delivered as storm tails from distal storm events. Outside of areas with high surface and deep eddy kinetic energy, benthic nepheloid layers are weak to non-existent, indicating that benthic storms are necessary to create and maintain strong nepheloid layers. Origins and intensities of benthic storms are best identified using a combination of time-series measurements of bottom currents, PM concentration, and bottom photographs, and these should be coupled with water-column and surface-circulation data to better interpret the specific relations between shallow and deep circulation patterns. Understanding the generation of benthic nepheloid layers is necessary in order to properly interpret PM distribution and its influence on global biogeochemistry.

58 GEOSCIENCES↗

DOE OSTI2013

Extending molecular simulation time scales: Parallel in time integrations for high-level quantum chemistry and complex force representations

Parallel in time simulation algorithms are presented and applied to conventional molecular dynamics (MD) and ab initio molecular dynamics (AIMD) models of realistic complexity. Assuming that a forward time integrator, f (e.g., Verlet algorithm), is available to propagate the system from time t{sub i} (trajectory positions and velocities x{sub i} = (r{sub i}, v{sub i})) to time t{sub i+1} (x{sub i+1}) by x{sub i+1} = f{sub i}(x{sub i}), the dynamics problem spanning an interval from t{sub 0}…t{sub M} can be transformed into a root finding problem, F(X) = [x{sub i} − f(x{sub (i−1})]{sub i} {sub =1,M} = 0, for the trajectory variables. The root finding problem is solved using a variety of root finding techniques, including quasi-Newton and preconditioned quasi-Newton schemes that are all unconditionally convergent. The algorithms are parallelized by assigning a processor to each time-step entry in the columns of F(X). The relation of this approach to other recently proposed parallel in time methods is discussed, and the effectiveness of various approaches to solving the root finding problem is tested. We demonstrate that more efficient dynamical models based on simplified interactions or coarsening time-steps provide preconditioners for the root finding problem. However, for MD and AIMD simulations, such preconditioners are not required to obtain reasonable convergence and their cost must be considered in the performance of the algorithm. The parallel in time algorithms developed are tested by applying them to MD and AIMD simulations of size and complexity similar to those encountered in present day applications. These include a 1000 Si atom MD simulation using Stillinger-Weber potentials, and a HCl + 4H{sub 2}O AIMD simulation at the MP2 level. The maximum speedup ((serial execution time)/(parallel execution time) ) obtained by parallelizing the Stillinger-Weber MD simulation was nearly 3.0. For the AIMD MP2 simulations, the algorithms achieved speedups of up to 14.3. The parallel in time algorithms can be implemented in a distributed computing environment using very slow transmission control protocol/Internet protocol networks. Scripts written in Python that make calls to a precompiled quantum chemistry package (NWChem) are demonstrated to provide an actual speedup of 8.2 for a 2.5 ps AIMD simulation of HCl + 4H{sub 2}O at the MP2/6-31G* level. Implemented in this way these algorithms can be used for long time high-level AIMD simulations at a modest cost using machines connected by very slow networks such as WiFi, or in different time zones connected by the Internet. The algorithms can also be used with programs that are already parallel. Using these algorithms, we are able to reduce the cost of a MP2/6-311++G(2d,2p) simulation that had reached its maximum possible speedup in the parallelization of the electronic structure calculation from 32 s/time step to 6.9 s/time step.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Towards Digital and Performance-Based Supervisory HVAC Control Delivery

Upgrading supervisory HVAC control in commercial buildings is one of the most attractive decarbonization tools at our disposal. Modern controls are software programs and can in theory be deployed at scale and with a low up-front carbon "pulse". In practice, however, control delivery is a disjointed and inefficient process, dominated by manual handoffs of imprecise English language documents. A particularly high barrier exists between control implementation and building energy modeling (BEM) which results in control sequences typically not being tested for correctness or performance before implementation. Together with industry partners, DOE and the national labs are developing an ecosystem of tools and standards that can support fully digital performance-based control delivery workflows. This paper describes this ecosystem, which consists of three mutually supportive efforts. Semantic models of buildings and their systems enable automatic configuration and installation of control software. Platform-neutral control descriptions separate control algorithms from control platforms and enable the creation of libraries of reference control implementations. Dynamic whole-building energy-control simulation that can execute physically realistic control sequences makes it possible to test and evaluate the performance of control sequences and then directly compile them for installation and execution in control systems. In addition to digitizing and streamlining project-level control delivery, these standards and related software support benchmarking of control algorithms, both rule-based and optimization-based, and help to both advance the state of the art and to implement ratings and programs that encourage the adoption of high-performance control.

building controls↗