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DOE OSTI2025

ChemComp: A Compilation Framework for Computing with Chemical Reaction Networks

The acceleration of scientific computation, data analytics, and artificial intelligence is driving a surge in computational requirements. Yet, state-of-the-art high-performance computing systems are approaching physical limitations that impede further significant improvements in energy efficiency. As we move towards post-exascale computing systems, innovative approaches are necessary to overcome this barrier in power consumption. Novel analog and hybrid digital-analog architectures hold promise for enhancing energy efficiency by several orders of magnitude. Biochemical computation stands out among the various solutions being explored due to its potential to enable new classes of devices with immense computational capabilities. These devices can capitalize on the inherent efficacy of biological cells in solving optimization problems and are scalable through increasing reaction system size or vessel capacity, potentially satisfying scientific computing's high-performance requirements. Nonetheless, several theoretical and practical limitations persist, including problem formulation and mapping to chemical reaction networks (CRNs) and implementation of actual CRN devices. In this paper, we propose a framework for biochemical computation using systems chemistry. We present the initial components of our approach: an abstract chemical reaction dialect implemented as a multi-level intermediate representation (MLIR) compiler extension and a pathway to represent mathematical problems with CRNs. To showcase the potential of this approach, we emulate a simplified chemical reservoir device. This work lays the groundwork for leveraging chemistry's computing potential in creating energy-efficient, high-performance computing systems tailored to contemporary computational needs.

artificial intelligence↗

DOE OSTI2020

ADREM

Analytical Data Reduction Excel Macro

Hobbs, Ian↗

DOE OSTI2020

Consistent Space Runtime (CSPACER) v1.0

This software provides a runtime for communication-bound applications, especially with irregular communication patterns. The target programming abstraction for the runtime is the space consistency model, which defines consistency guarantees at the granularity of memory spaces. This model has relaxed consistency semantics that enables a wide range of runtime optimizations. The runtime leverages threading to accelerate communication primitives, especially collective operations. It also allows efficient pipelining of communication operations and enable constructing a consistent state of multiple unordered communication activities targeting a memory space. The runtime uses a reduced API design that decomposes complex communication primitives in traditional general-purpose runtime into a sequence of simpler steps. To improve the productivity of using this runtime, we provide communication patterns commonly used for regular scientific computing applications and irregular data analytics. These communication patterns offer skeletons for the integration with application computation to allow efficient overlap.

Ibrahim, Khaled↗

DOE OSTI2022

MPC4CLR (Model-Predictive-Control-for-Critical-Load-Restoration-in-Power-Distribution-Systems) [SWR-22-24]

Model predictive control (MPC) is a system or process control technique for making decisions under uncertainty via rolling look-ahead optimizations at each control step where only the current step decisions are applied, and the rest are discarded. In this work, we developed an MPC for a critical load restoration (CLR) in power distribution systems to recover system service (electricity delivery) following an extreme event-triggered substation outage. The method considers the problem of controlling distributed energy resources (DERs) of the distribution system with the objective of achieving maximum load pick up while satisfying distribution network flow and voltage constraints. A linearized optimal power flow (OPF) model is employed to represent the physics of the network. The problem formulation is augmented with a ramping (up) reserve product for the DERs to ensure improved and upward monotonic load restoration as time evolves. Simulation analysis and performance tests are performed using a modified IEEE 13-bus test feeder integrated with wind, solar, microturbine, and energy storage battery. The software is developed using various software packages in Julia and Python. The MPC model is implemented using the JuMP optimization language in Julia while the data analytics including renewable generation and load demand forecasts, running the MPC simulation and visualizations is performed in Python.

Eseye, Abinet Tesfaye↗

DOE OSTI2022

SOCRATES

SOCRATES is a Suite Of Comprehensive Rapid Analysis Tools for Environmental Sites. It provides tools to retrieve, filter, select, and view Hanford data and to perform multiple types of data analyses. SOCRATES currently includes four data analytics modules

Royer, Patrick↗

DOE OSTI2020

Cyber Awareness Visualization And Event Action Tool

This tool allows the simplified and informed visualization of any data analytics tool with the ability to match the CAVEAT format. CAVEAT is capable of having any kind of control room configured with any arbitrary number of control surfaces.

Lehmer, JacobP.↗

DOE OSTI2020

Monitoring the Caustic Dissolution of Aluminum Alloy in a Radiochemical Hot Cell Using Raman Spectroscopy

Chemical processing of highly radioactive materials commonly takes place in heavily shielded hot cells. The remote, real-time monitoring of chemical processing streams via optical spectroscopic techniques in hot cells may be particularly useful. Here in this paper, we describe the implementation of Raman spectroscopy and chemometric analysis to monitor the dissolution of aluminum-clad targets containing irradiated aluminum–neptunium oxide cermet pellets in caustic solutions in a hot cell environment. Partial least squares regression analysis was used to generate calibration models to quantify the concentration of dissolved aluminum, nitrate, and hydroxide in solutions within the radiochemical hot cell. This work explored a systematic approach to optimize a matrix of calibration standards using a D-optimal experimental design. The Design of Experiments-based regression model, in comparison to more traditional analytical approaches, was found to be the more practical method for building calibration models, with fewer samples, to obtain informative analytical data from Raman spectra.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Dimensionally reduced machine learning model for predicting single component octanol–water partition coefficients

Abstract MF-LOGP, a new method for determining a single component octanol–water partition coefficients ( $$LogP$$ LogP ) is presented which uses molecular formula as the only input. Octanol–water partition coefficients are useful in many applications, ranging from environmental fate and drug delivery. Currently, partition coefficients are either experimentally measured or predicted as a function of structural fragments, topological descriptors, or thermodynamic properties known or calculated from precise molecular structures. The MF-LOGP method presented here differs from classical methods as it does not require any structural information and uses molecular formula as the sole model input. MF-LOGP is therefore useful for situations in which the structure is unknown or where the use of a low dimensional, easily automatable, and computationally inexpensive calculations is required. MF-LOGP is a random forest algorithm that is trained and tested on 15,377 data points, using 10 features derived from the molecular formula to make $$LogP$$ LogP predictions. Using an independent validation set of 2713 data points, MF-LOGP was found to have an average $$RMSE$$ RMSE = 0.77 ± 0.007, $$MAE$$ MAE = 0.52 ± 0.003, and $${R}^{2}$$ R 2 = 0.83 ± 0.003. This performance fell within the spectrum of performances reported in the published literature for conventional higher dimensional models ( $$RMSE$$ RMSE = 0.42–1.54, $$MAE$$ MAE = 0.09–1.07, and $${R}^{2}$$ R 2 = 0.32–0.95). Compared with existing models, MF-LOGP requires a maximum of ten features and no structural information, thereby providing a practical and yet predictive tool. The development of MF-LOGP provides the groundwork for development of more physical prediction models leveraging big data analytical methods or complex multicomponent mixtures. Graphical Abstract

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

SEM and STEM X-ray spectrum images

This is supplemental information to a paper tentatively titled Applying Data Analytics Methods to X-ray Spectrum Images. Datasets are in the format of .h5 in the pyUSID flavor. SEM_small.h5 is 5 keV beam energy map of a TiB2 ceramic puck. SEM_large.h5 is a 20 keV map of the same sample. STEM.h5 is a STEM 200 keV map of neutron-irradiated tungsten (due to transmutation burnout, it has become a W-Re-Os alloy).

36 MATERIALS SCIENCE↗

DOE OSTI2021

Evaluation of “Tight Oil” Well Performance and Completion Practices in the Powder River Basin - “Time Slice” Analysis

The objective of this paper is to assess how well completion practices and well performance have evolved over time (“time slices”) in the tight sands and shales of the Powder River Basin (PRB). This information can provide a foundation for helping operators define more effective well completion practices and thus optimize well performance in an emerging “tight oil” basin. To start, the authors assembled a “database” containing well completion practices, production data, and geologic information for more than 800 horizontal (Hz) wells targeting three “tight oil” formations -- Turner, Frontier, and Mowry--placed on production in the past dozen years. To control for the impact of geologic and reservoir properties on well performance, the authors defined 12 geologically distinct areas (“partitions”) for the Turner, Frontier, and Mowry Shale in the Powder River Basin (4 partitions in each formation). This paper discusses the methodology for establishing “time slices” for each partition within each of the three “tight oil” formations, including (1) taking out, to the extent practical, the effects of geology by partitioning the three “tight oil” formations based on their geologic parameters; (2) using type curves and estimated ultimate recoveries (EURs) to establish a reliable measure of well performance; and (3) rigorously inspecting the production and well completion data to assure a quality dataset. Partition #2, a high thermal maturity area of the Frontier Sandstone in the western Powder River Basin, helps illustrate the results of the study. Using a dataset of 55 Hz wells, the study found that well performance has steadily improved, with oil EURs increasing from 180 MBbl in 2012-13 to 290 MBbl in 2018-19. Much of this improvement was due to the use of longer Hz laterals, increasing notably from 3,765 ft in 2012-13 to 10,260 ft in 2018-19. More intensive completion practices contributed, as well. For example, the number of frac stages more than doubled, from 17 to 35, and proppant concentrations increased from 1,060 lbs/ft to 1,320 lbs/ft. Finally, the data show diminishing returns to longer laterals and more intensive completion practices. For example, the key performance measure of oil EUR per 1,000 ft of lateral is decreasing. For 2012-13, Hz wells recovered 50 MBbl of oil per 1,000 ft of lateral while the more recent 2018-19 Hz wells only provide 30 MBbl of oil per 1,000 ft of lateral. Considerable insight can be gained by using “time slices” and geologic partitioning to better understand the relationship between changes in well drilling and completion practices and changes in well performance in emerging “tight oil” plays. The results from this study can also serve as a foundation for subsequent, more intense efforts involving data analytics for defining more optimum well completion practices targeting specified geologic settings and formations.

02 PETROLEUM↗

DOE OSTI2016

Emerging operando and x-ray pair distribution function methods for energy materials development

Our energy needs drive widespread materials research. Advances in materials characterization are critical to this research effort. Using new characterization tools that allow us to probe the atomic structure of energy materials in situ as they operate, we can identify how their structure is linked to their functional properties and performance. These fundamental insights serve as a roadmap to enhance performance in the next generation of advanced materials. In the last decade, developments in synchrotron instrumentation have made the pair distribution function (PDF) method and operando x-ray studies more readily accessible tools capable of providing valuable insights into complex materials systems. Here, the emergence of the PDF method as a versatile structure characterization tool and the further enhancement of this method through developments in operando capabilities and multivariate data analytics are described. These advances in materials characterization are demonstrated by several highlighted studies focused on energy storage in batteries.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Practical procedures for sensor quality assessment

Sensors are increasingly deployed for process monitoring and control. These produce on-line measurements at a high frequency, in parallel with low-frequency laboratory measurements. Compared to laboratory practices, sensor data quality assessment and control practices are far less structured at most utilities. This leads to inaccurate sensor data with unknown uncertainty factors.This chapter shows how to establish standard operating procedures (SOPs) to support sensor data quality assessment and control and subsequent maintenance actions by producing relevant sensor metadata. Furthermore, SOPs are provided for the most commonly used wastewater quality sensors, inspired by utility and academic best practices. This chapter builds on definitions provided in Chapter 3 and provides additional definitions specifically related to sensors maintenance. Chapter 6 complements the methods in this chapter, which are based on reference measurements, with data-analytical techniques.

Alferes, Janelcy↗

DOE OSTI2012

Annual Storm Water Report for the Y-12 National Security Complex Oak Ridge, Tennessee

The storm water pollution prevention program at the Y-12 National Security Complex (Y-12 Complex) intends to protect the quality of storm water runoff through: (1) reducing the exposure of metal accumulation areas to precipitation, (2) implementation of Best Management Practices, (3) sampling during rain events and subsequent analysis, and (4) routine surveillances. When prescribed, the analytical data is compared to a set of cut-off concentration values to determine how the Y-12 Complex relates to other metal fabrication industries in the state of Tennessee. The quality of the storm water exiting the Y-12 Complex via East Fork Poplar Creek indicated some improvement in 2011. This improvement is attributable to the completion of several construction, demolition and remediation projects which occurred in 2010 and 2011. Emphasis will continue to be placed on site inspections and the timely implementation of improved storm water control measures as deemed necessary.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2012

Annual Storm Water Report for the Y-12 National Security Complex, Oak Ridge, Tennessee

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2012

Analyses of HTF-48-12-20/24 (February, 2012) and Archived HTF-E-05-021 Tank 48H Slurry Samples

Personnel characterized a Savannah River National Laboratory (SRNL) archived sample of Tank 48H slurry (HTF-E-05-021) in addition to the composite of samples HTF-48-12-20 and HTF-48-12-24, which were both retrieved in February 2012. The combined February 2012 sample is referred to as HTF-48-12-20/24 in this report. The results from these analyses are compared with Tank 48H samples analyzed in 2003, 2004, and 2005. This work supports the effort to demonstrate copper-catalyzed peroxide oxidation (CCPO) of organic content in this material. The principal findings with respect to the chemical and physical characteristics of the most recent sample are: (1) The measured potassium tetraphenylborate (KTPB) solid concentration is 1.76 wt %; (2) Titanium was in line with 2004 and 2005 slurry measurements at 897 mg/L, it represents 0.1535 ± 0.0012 wt % monosodium titanate (MST); (3) The measured insoluble solids content was 1.467 wt %; (4) The free hydroxide concentration in the Tank 48H filtrate sample (1.02 ± 0.02 M) is close to the Tank 48H limit (1.0 M); (5) Carbonate reported by total inorganic carbon (TIC, 1.39 ± 0.03 M) is more than double the concentrations measured in past (2003-2005) samples; (6) The soluble potassium content (measured at 286 ± 23 mg/L) in the filtrate is in line with all past measurements; and (7) The measured 137 Cs concentration is 7.81E + 08 ± 3.9E + 07 dpm/mL of slurry (1.33 ± 5% Ci/gallon or 3.18E + 05 ± 5% curies of 137 Cs in the tank) in the slurry which is in agreement with the 2005 report of 3.14E + 05 ± 1.5% curies of 137 Cs in the tank. The filtrate 137 Cs concentration is 2.57E + 07 ± 2.6E + 05 dpm/mL. This result is consistent with previous results. Significant analytical data are summarized in Table 1.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2013

Tank 30 and 37 Supernatant Sample Cross-Check and Evaporator Feed Qualification Analysis (2012)

This report summarizes the analytical data reported by the F/H and Savannah River National Laboratories for the 2012 cross-check analysis for high level waste supernatant liquid samples from SRS Tanks 30 and 37. The intent of this Tank 30 and 37 sample analyses was to perform cross-checks against routine F/H Laboratory analyses (corrosion and evaporator feed qualification programs) using samples collected at the same time from both tanks as well as split samples from the tanks.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2013

Rapid Analysis of Ash Composition Using Laser-Induced Breakdown Spectroscopy (LIBS)

Inorganic compounds are known to be problematic in the thermochemical conversion of biomass to syngas and ultimately hydrocarbon fuels. The elements Si, K, Ca, Na, S, P, Cl, Mg, Fe, and Al are particularly problematic and are known to influence reaction pathways, contribute to fouling and corrosion, poison catalysts, and impact waste streams. Substantial quantities of inorganic species can be entrained in the bark of trees during harvest operations. Herbaceous feedstocks often have even greater quantities of inorganic constituents, which can account for as much as one-fifth of the total dry matter. Current methodologies to measure the concentrations of these elements, such as inductively coupled plasma-optical emission spectrometry/mass spectrometry (ICP-OES/MS) are expensive in time and reagents. This study demonstrates that a new methodology employing laser-induced breakdown spectroscopy (LIBS) can rapidly and accurately analyze the inorganic constituents in a wide range of biomass materials, including both woody and herbaceous examples. This technique requires little or no sample preparation, does not consume any reagents, and the analytical data is available immediately. In addition to comparing LIBS data with the results from ICP-OES methods, this work also includes discussions of sample preparation techniques, calibration curves for interpreting LIBS spectra, minimum detection limits, and the use of internal standards and standard reference materials.

09 BIOMASS FUELS↗

DOE OSTI2013

Annual Storm Water Report for the Y-12 National Security Complex, Oak Ridge, Tennessee (Rev.7)

This is the second annual storm water report prepared in accordance with the National Pollutant Discharge Elimination System (NPDES) permit issued to the Y-12 National Security Complex (Y-12 Complex) on December 1, 2011, and the corresponding Y-12 Storm Water Pollution Prevention Plan (SWP3) which became effective on September 7, 2012. However, Appendix A does contain some analytical data gathered under the previous NPDES permit and SWP3 for comparison purposes. The quality of storm water exiting the Y-12 Complex via East Fork Poplar Creek remained relatively stable from 2012 to 2013. However, there was one largely unexpected high concentration of mercury noted in an area that is not known to have previously been a mercury use area. This was noted in Sector AA, Outfall 014. This outfall is normally sampled on a rotating basis but, due this elevated concentration, will be sampled again in 2014. The Y-12 Complex will continue to implement appropriate BMPs and reduce outside material storage areas where possible. Emphasis will continue to be placed on site inspections and timely implementation of proper storm water control measures.

54 ENVIRONMENTAL SCIENCES↗