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DOE OSTI2012

Sensor placement algorithm development to maximize the efficiency of acid gas removal unit for integrated gasifiction combined sycle (IGCC) power plant with CO2 capture

Future integrated gasification combined cycle (IGCC) power plants with CO{sub 2} capture will face stricter operational and environmental constraints. Accurate values of relevant states/outputs/disturbances are needed to satisfy these constraints and to maximize the operational efficiency. Unfortunately, a number of these process variables cannot be measured while a number of them can be measured, but have low precision, reliability, or signal-to-noise ratio. In this work, a sensor placement (SP) algorithm is developed for optimal selection of sensor location, number, and type that can maximize the plant efficiency and result in a desired precision of the relevant measured/unmeasured states. In this work, an SP algorithm is developed for an selective, dual-stage Selexol-based acid gas removal (AGR) unit for an IGCC plant with pre-combustion CO{sub 2} capture. A comprehensive nonlinear dynamic model of the AGR unit is developed in Aspen Plus Dynamics® (APD) and used to generate a linear state-space model that is used in the SP algorithm. The SP algorithm is developed with the assumption that an optimal Kalman filter will be implemented in the plant for state and disturbance estimation. The algorithm is developed assuming steady-state Kalman filtering and steady-state operation of the plant. The control system is considered to operate based on the estimated states and thereby, captures the effects of the SP algorithm on the overall plant efficiency. The optimization problem is solved by Genetic Algorithm (GA) considering both linear and nonlinear equality and inequality constraints. Due to the very large number of candidate sets available for sensor placement and because of the long time that it takes to solve the constrained optimization problem that includes more than 1000 states, solution of this problem is computationally expensive. For reducing the computation time, parallel computing is performed using the Distributed Computing Server (DCS®) and the Parallel Computing® toolbox from Mathworks®. In this presentation, we will share our experience in setting up parallel computing using GA in the MATLAB® environment and present the overall approach for achieving higher computational efficiency in this framework.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2012

Sensor placement algorithm development to maximize the efficiency of acid gas removal unit for integrated gasification combined cycle (IGCC) power plant with CO{sub 2} capture

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2016

Method for maximizing the brightness of the bunches in a particle injector by converting a highly space-charged beam to a relativistic and emittance-dominated beam

A method for maximizing the brightness of the bunches in a particle injector by converting a highly space-charged beam to a relativistic and emittance-dominated beam. The method includes 1) determining the bunch charge and the initial kinetic energy of the highly space-charge dominated input beam; 2) applying the bunch charge and initial kinetic energy properties of the highly space-charge dominated input beam to determine the number of accelerator cavities required to accelerate the bunches to relativistic speed; 3) providing the required number of accelerator cavities; and 4) setting the gradient of the radio frequency (RF) cavities; and 5) operating the phase of the accelerator cavities between -90 and zero degrees of the sinusoid of phase to simultaneously accelerate and bunch the charged particles to maximize brightness, and until the beam is relativistic and emittance-dominated.

43 PARTICLE ACCELERATORS↗

DOE OSTI2019

Optimally placing photovoltaic arrays to maximize value of energy production based on peak power production, local solar radiation, weather, electricity market prices and rate structures

A method, system and computer program product for optimally placing photovoltaic arrays to maximize a value of energy production. Incident solar radiation for various placements of the photovoltaic arrays accommodating different azimuths and tilts is calculated. Alternating current solar photovoltaic electricity energy and power production is then estimated from the calculated solar radiation on a plane and weather data. Furthermore, a value of solar photovoltaic electricity energy and power produced by the photovoltaic arrays for the various placements is calculating using the estimated alternating current solar photovoltaic electricity production. A placement out of the various placements for the photovoltaic arrays is then selected corresponding to a highest value of the solar photovoltaic electricity produced by the photovoltaic arrays. In this manner, the appropriate placement for the photovoltaic arrays is determined that maximizes the value of energy production (where “value” may correspond to an economic value or a non-economic value).

Webber, Michael E.↗

DOE OSTI2019

Calculating Dose Release Factors to Obtain the Worst-Case Maximally Exposed Location by Sector

The aim of this project was to update the SRS Dose Release Factors (DRF's) for the Maximally Exposed Individual (MEI) for 20 area release points onsite. To update, potential MEIs now include onsite locations and modeled stack heights were updated to match onsite operations. The DRF's and MEI locations are used to ensure DOE and EPA compliance is met for dose standards. The Environmental Protection Agency (EPA) requires the use of the computer model CAP88 to estimate doses for demonstrating compliance with 40 CFR 61, the National Emission Standard for Hazardous Air Pollutants (NESHAP). The location of the maximally exposed individual (MEI) by sector and distance is required for execution of CAP88. The worst-case sector is the sector and distance where an offsite individual would receive the highest dose due to a potential release from a designated release location at a facility. The worst-case sector analysis addresses potential ground-level and stack-height releases from 20 areas of Savannah River Site (SRS). Weather patterns were analyzed at each of these areas relative to sixteen compass points. The analysis makes use of recently updated distance data and meteorological data. The computer model, CAP88 is EPA's software system used by the Department of Energy (DOE) to calculate the receptor dose due to routine atmospheric releases via a gaussian plume at the Savannah River Site (SRS). The dose-release factors (DRFs) are used to estimate the offsite and onsite dose from facility-specific releases and represent the dose to a receptor exposed to 1 Ci of a specified radionuclide being released into the atmosphere. The DRFs are simply a ratio of the TED to the release rate and, therefore, are directly scalable. The DRF values listed in the Appendix can be applied to expected release values from each area to estimate the potential dose to an individual adult at each location. NESHAP DRFs have been supplied to Environmental Compliance and Area Closure Projects (EC and ACP) for many years and are periodically updated to include changes in Cap88. estimate the potential dose to an individual adult at each location DRF in mrem Ci{sup -1} are estimated by modeling the total effective dose (TED) in mrem yr{sup -1} assuming an annual atmospheric release rate of 1 Ci yr-1 of the associated radionuclides. TED = Effective Dose (ED) + Committed Effective Dose (CED). TED = DRF/RR. Approach and Methods: Determine possible MEI locations Onsite/Offsite including buildings and farms; Determine the distances from the release area to the possible MEI location and the direction from the release to the MEI location; Using the most recent meteorological data (2007-2011) and parameters, run CAP88 for each release area for each compass sector and previously calculated distances to MEI locations using a 1 Ci release rate for tritium; Use the calculated the air concentration values to determine the MEI for each sector from CAP88. The relationship between air concentration and received dose is directly proportional and can be used to determine which locations to calculate DRF's and a dose for an MEI; The DRFs are found for each compass sector from 20 SRS release areas using CAP88-PC Version 4.0; Each location is calculated with ground level releases evaluated for each area for a list of radionuclides, some with and some without progenies; Compare the DRFs of the potential onsite MEIs to offsite MEIs. Based on the 2018 MEI Report, the Site worst case sector MEI is located 593 mW of B-Area. This MEI location represents a point along the main road that travels through a tract of land leased to the SC National Guard. While this location is estimated to have the highest exposure, minimal radioactivity is released from B-Area. In 2017, SRS requested and was approved by the EPA to change the location for modeling site releases from the Center of Site to H-Area, and to use six stack heights. H-Area emission account for approximately 90% of all radioactive operations onsite. The MEI for H-Area was found to be 11,458 m NNE which locates the Savannah River Ecology Lab Conference Center. Comparisons for 2018 data and 2014 shows the new methods of calculation are more conservative yet still remain well below the DOE 100 mrem limit.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Debiasing Watermarks for Large Language Models via Maximal Coupling

Watermarking language models is essential for distinguishing between human and machine-generated text and thus maintaining the integrity and trustworthiness of digital communication. Here, we present a novel green/red list watermarking approach that partitions the token set into “green” and “red” lists, subtly increasing the generation probability for green tokens. To correct token distribution bias, our method employs maximal coupling, using a uniform coin flip to decide whether to apply bias correction, with the result embedded as a pseudorandom watermark signal. Theoretical analysis confirms this approach’s unbiased nature and robust detection capabilities. Experimental results show that it outperforms prior techniques by preserving text quality while maintaining high detectability, and it demonstrates resilience to targeted modifications aimed at improving text quality. This research provides a promising watermarking solution for language models, balancing effective detection with minimal impact on text quality.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Dragonfly : an implementation of the expand–maximize–compress algorithm for single-particle imaging

Single-particle imaging (SPI) with X-ray free-electron lasers has the potential to change fundamentally how biomacromolecules are imaged. The structure would be derived from millions of diffraction patterns, each from a different copy of the macromolecule before it is torn apart by radiation damage. The challenges posed by the resultant data stream are staggering: millions of incomplete, noisy and un-oriented patterns have to be computationally assembled into a three-dimensional intensity map and then phase reconstructed. In this paper, the Dragonfly software package is described, based on a parallel implementation of the expand–maximize–compress reconstruction algorithm that is well suited for this task. Auxiliary modules to simulate SPI data streams are also included to assess the feasibility of proposed SPI experiments at the Linac Coherent Light Source, Stanford, California, USA.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2017

Distributed-Memory Fast Maximal Independent Set

The Maximal Independent Set (MIS) graph problem arises in many applications such as computer vision, information theory, molecular biology, and process scheduling. The growing scale of MIS problems suggests the use of distributed-memory hardware as a cost-effective approach to providing necessary compute and memory resources. Luby proposed four randomized algorithms to solve the MIS problem. All those algorithms are designed focusing on shared-memory machines and are analyzed using the PRAM model. These algorithms do not have direct efficient distributed-memory implementations. In this paper, we extend two of Luby’s seminal MIS algorithms, “Luby(A)” and “Luby(B),” to distributed-memory execution, and we evaluate their performance. We compare our results with the “Filtered MIS” implementation in the Combinatorial BLAS library for two types of synthetic graph inputs.

distributed memory parallel↗

DOE OSTI2014

MaxBin: an automated binning method to recover individual genomes from metagenomes using an expectation-maximization algorithm

Recovering individual genomes from metagenomic datasets allows access to uncultivated microbial populations that may have important roles in natural and engineered ecosystems. Understanding the roles of these uncultivated populations has broad application in ecology, evolution, biotechnology and medicine. Accurate binning of assembled metagenomic sequences is an essential step in recovering the genomes and understanding microbial functions. We have developed a binning algorithm, MaxBin, which automates the binning of assembled metagenomic scaffolds using an expectation-maximization algorithm after the assembly of metagenomic sequencing reads. Binning of simulated metagenomic datasets demonstrated that MaxBin had high levels of accuracy in binning microbial genomes. MaxBin was used to recover genomes from metagenomic data obtained through the Human Microbiome Project, which demonstrated its ability to recover genomes from real metagenomic datasets with variable sequencing coverages. Application of MaxBin to metagenomes obtained from microbial consortia adapted to grow on cellulose allowed genomic analysis of new, uncultivated, cellulolytic bacterial populations, including an abundant myxobacterial population distantly related to Sorangium cellulosum that possessed a much smaller genome (5 MB versus 13 to 14 MB) but has a more extensive set of genes for biomass deconstruction. For the cellulolytic consortia, the MaxBin results were compared to binning using emergent self-organizing maps (ESOMs) and differential coverage binning, demonstrating that it performed comparably to these methods but had distinct advantages in automation, resolution of related genomes and sensitivity. The automatic binning software that we developed successfully classifies assembled sequences in metagenomic datasets into recovered individual genomes. The isolation of dozens of species in cellulolytic microbial consortia, including a novel species of myxobacteria that has the smallest genome among all sequenced aerobic myxobacteria, was easily achieved using the binning software. This work demonstrates that the processes required for recovering genomes from assembled metagenomic datasets can be readily automated, an important advance in understanding the metabolic potential of microbes in natural environments. MaxBin is available at https://sourceforge.net/projects/maxbin/.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Data for Determining Spatially Varying Profit-Maximizing Management Practices for Miscanthus and Switchgrass Production in the Rainfed United States

The compiled datasets include county-level variables used for simulating miscanthus and switchgrass production in 2287 counties across the rainfed US including 5-year (2012-2016) averaged growing season degree days (GDD), 5-year (2012-2016) averaged growing season cumulative precipitation, National Commodity Crop Productivity Index (NCCPI) values, regional dummies (only for miscanthus), the regional-level random effect of the yield response function, N price, land cash rent, the first year fixed cost (only for switchgrass), and separate datasets for simulating an alternative model assuming a constant N rate. The GAMS codes are used to run the simulation to obtain the main results including the age-varying profit-maximizing N rate, biomass yields, and annual profits for miscanthus and switchgrass production across counties in the rainfed US. The STATA codes are used to merge and analyze simulation results and create summary statistics tables and key figures.

Age↗

DOE OSTI2021

Validation of Volterra (now Maxim) Modules at the Regional Test Centers (CRADA CRD-13-00531 Final Report)

Volterra (now Maxim), Sandia National Laboratories, and the National Renewable Energy Laboratory are entering into a cooperative research and development agreement (CRADA) in order to perform validation testing of Volterra’s PV modules through the DOE Regional Test Centers (RTCs).

14 SOLAR ENERGY↗

NASA NTRS2019

A Joinable Undercarriage to Maximize Payload (JUMP) Lunar Lander for Cargo Delivery to the Lunar Surface

Currently, NASA has engaged industry to develop a series of small to medium capacity landers with payload capacities of up to 5-9 tons by the mid to late 2020s. This contrasts with the former Constellation program, where the Altair lunar lander was targeting a payload capability of roughly 14-20 tons. Investment in smaller landers may present future challenges in delivering habitat modules larger than lunar lander cabins or small logistics modules to the lunar surface. Additionally, given a projected SLS flight rate of 1-2 launches per year, a lunar surface buildup from small elements seems problematic at best. While commercial launchers provide a supplement to SLS, many of the current and projected launch vehicles deliver less than 20 tons to a Trans-Lunar Injection – even fewer to the lunar surface. However, a possible solution could emerge if the lander itself could be launched in pieces with a buildup in Cislunar space. Thus, launchers with these capacities could contribute to a lunar lander capable of delivering 30 tons or more to the lunar surface. This paper introduces the notional concept of a Joinable Undercarriage to Maximized Payload (JUMP) lander. Key elements of a proposed JUMP lander concept will be discussed, followed by recommendations and forward work.

Human spaceflight↗

DOE OSTI2017

Parallel Asynchronous Distributed-Memory Maximal Independent Set Algorithm with Work Ordering

The maximal independent set (MIS) graph problem arises in many applications such as computer vision, information theory, molecular biology, and process scheduling. The growing scale of graph data suggests the use of distributed memory hardware as a cost-effective approach to providing necessary compute and memory resources. Existing distributed memory parallel MIS algorithms rely on synchronous communication and use techniques such as subgraph computations. In this paper, we present an asynchronous distributed-memory parallel graph algorithm that relies on a virtual directed acyclic graph (DAG) that is created during the algorithm execution. We introduce two additional algorithms that save computations by ordering generated work. The first algorithm applies ordering globally to reduce computations, and the second algorithm applies ordering locally at the level of threads to minimize the synchronization overhead. We use two different implementations of Luby’s algorithm variants as baseline to compare the performance of the presented algorithms: (1) vertex-centric Luby A and Luby B implementations, and (2) the CombBLAS linear-algebra Luby A implementation. Results show that proposed algorithms outperform both implementations of Luby algorithms, especially in distributed execution. Furthermore, we show that for low-diameter graphs the algorithm that applies global ordering scales better than other algorithms and for high diameter graphs the original asynchronous algorithm and thread-level ordering algorithm show better performance.

maximal independent set (MIS), distributed memory ↗

DOE OSTI2019

Entropy‐Maximized Synthesis of Multimetallic Nanoparticle Catalysts via a Ultrasonication‐Assisted Wet Chemistry Method under Ambient Conditions

Abstract A facile ultrasonication‐assisted wet chemistry method for preparing multicomponent alloy nanoparticles (NPs) including high‐entropy alloys (HEAs) is reported. PtAuPdRhRu alloy (HEA), quaternary PtAuPdRh alloy, and ternary PtAuPd alloy NPs are produced with ≈3 nm in diameter. Taking advantage of the acoustic cavitation phenomenon in ultrasonication process, noble metal precursors could be co‐reduced by chemical reductants and transform to alloy structures under operation at room conditions. The instantaneous massive energy (≈5000 °C, 2000 atm) occurring in momentary timespans (≤10 −9 s) contributes to the formation of multimetallic mixed nanomaterials driven by entropy maximization. Owing to strong synergistic effects, the catalysts with the HEA NPs supported on carbons exhibit prominent electrocatalytic activities for hydrogen evolution reaction.

Liu, Miaomiao↗

DOE OSTI2021

Reimagining the $e_g$ 1 Electronic State in Oxygen Evolution Catalysis: Oxidation-State-Modulated Superlattices as a New Type of Heterostructure for Maximizing Catalysis

We report that the discovery of solid-phase, inexpensive transition-metal-based water oxidation catalysts is a central goal for renewable energy, and has led to a general consensus that a partially populated metal e g d-electronic state is desirable, leading to favorable catalysis for certain elements in specific oxidation states. In manganese systems, the key species is manganese(III), whose high-spin d 4 electronic configuration places an unpaired electron in the e g orbital, which is postulated to contribute to electronic and structural features that support catalysis. Based on density functional theory calculations, it is predicted that electron transfer would be facilitated by a catalyst with alternating low- and high-Mn III -content sheets, which positions neighboring band edges in closer energetic proximity. The preparation of such catalysts is demonstrated for the first time and it is shown that the catalytic activity is maximized in these systems over more uniform, but more Mn III -rich systems. The best catalyst possesses alternating high-and low-average oxidation state sheets with interlayer Cs + ions, and has an overpotential of 450 mV at 10 mA, which represents an improvement of 250 mV over the best unmodified synthetic potassium birnessites. Using scanning tunneling spectroscopy, bandgap modulations consistent with the theoretically predicted band edge shifts are detected.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Floatable Protective Layers: a Strategy to Minimize Solid Electrolyte Interphase Growth and Maximize the Lithium Utilization

Abstract Maximizing lithium (Li) utilization is crucial for enhancing the long‐term stability of Li‐based batteries. In anode‐free Li batteries (AFLBs), although the initial formation of solid electrolyte interphase (SEI) is beneficial on limiting further reaction between Li and electrolyte, large volume change of Li metal anode (LMA) during cycling often leads to continuous breakdown and re‐formation of SEI and formation of inactive Li, hindering its efficiency. In this study, a novel strategy is presented to protect Li metal by applying a floatable protection layer (FPL) on a copper substrate, enabling large Li particles to be primarily deposited below FPL, but SEI to be primarily formed above FPL. This approach effectively minimizes the direct contact between electrolyte and freshly deposited Li, therefore mitigating the continuous side reactions and early failure of AFLBs. As a result, Li consumption is minimized, and the overall stability of the battery is significantly enhanced. Further development of this approach can also be used to improve the performance of other Li‐based batteries for large‐scale applications.

Lim, Hyung‐Seok [Energy and Environment Directorat↗

DOE OSTI2022

Likelihood Maximization and Moment Matching in Low SNR Gaussian Mixture Models

We derive an asymptotic expansion for the log-likelihood of Gaussian mixture models (GMMs) with equal covariance matrices in the low signal-to-noise regime. The expansion reveals an intimate connection between two types of algorithms for parameter estimation: the method of moments and likelihood optimizing algorithms such as Expectation-Maximization (EM). We show that likelihood optimization in the low SNR regime reduces to a sequence of least squares optimization problems that match the moments of the estimate to the ground truth moments one by one. This connection is a stepping stone towards the analysis of EM and maximum likelihood estimation in a wide range of models. A motivating application for the study of low SNR mixture models is cryo-electron microscopy data, which can be modeled as a GMM with algebraic constraints imposed on the mixture centers. We discuss the application of our expansion to algebraically constrained GMMs, among other example models of interest. © 2022 The Authors. Communications on Pure and Applied Mathematics published by Wiley Periodicals LLC.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

The principle of maximal transcendentality and the four-loop collinear anomalous dimension

Here, we use the principle of maximal transcendentality and the universal nature of subleading infrared poles to extract the analytic value of the four-loop collinear anomalous dimension in planar N = 4 super-Yang-Mills theory from recent QCD results, obtaining $\hat{g}$$(4)\atop{0}$ =$-$300ζ 7 $-$256ζ 2 ζ 5 $-$384ζ 3 ζ 4 . This value agrees with a previous numerical result to within 0.2%. It also provides the Regge trajectory, threshold soft anomalous dimension and rapidity anomalous dimension through four loops.

1/N Expansion↗