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DOE OSTI2019

Advancing Genome-Resolved Metagenomics beyond the Shotgun

Exploration of environmental microbiomes has shed light on the ecological and evolutionary principles at play in natural ecosystems and has been further accelerated through the reconstruction of population genomes to provide genome-centric context. Yet technical challenges with traditional shotgun metagenomics remain for computationally intense short-read assembly, strain heterogeneity within communities, and depth of coverage required for low-abundance microbes. In this Perspective, we highlight three main avenues for promising future developments, including coupling stable isotope probing and genome-resolved metagenomics, applying fluorescence-activated cell sorting approaches to target mini-metagenomes within a larger community, and utilizing single-molecule long-read and synthetic long-read technology to link mobile elements to host microbial cells. These developments on the horizon will undoubtedly advance genome-resolved metagenomic approaches and enable a better understanding of uncultivated microbes in their natural environments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Inhibiting and Remodeling Toxic Amyloid-Beta Oligomer Formation Using a Computationally Designed Drug Molecule That Targets Alzheimer’s Disease

Alzheimer’s disease (AD) is rapidly reaching epidemic status among a burgeoning aging population. Much evidence suggests the toxicity of this amyloid disease is most influenced by the formation of soluble oligomeric forms of amyloid β-protein, particularly the 42-residue alloform (Aβ42). Developing potential therapeutics in a directed, streamlined approach to treating this disease is necessary. Here we utilize the joint pharmacophore space (JPS) model to design a new molecule [AC0107] incorporating structural characteristics of known Aβ inhibitors, blood-brain barrier permeability, and limited toxicity. To test the molecule’s efficacy experimentally, we employed ion mobility mass spectrometry (IM-MS) to discover [AC0107] inhibits the formation of the toxic Aβ42 dodecamer at both high (1:10) and equimolar concentrations of inhibitor. Atomic force microscopy (AFM) experiments reveal that [AC0107] prevents further aggregation of Aβ42, destabilizes preformed fibrils, and reverses Aβ42 aggregation. This trend continues for long-term interaction times of 2 days until only small aggregates remain with virtually no fibrils or higher order oligomers surviving. Pairing JPS with IM-MS and AFM presents a powerful and effective first step for AD drug development. .

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Ionic current in nanochannels grafted with pH-responsive polyelectrolyte brushes modeled using augmented strong stretching theory

Here, we provide a theory to quantify the ionic current (i ion ) in nanochannels grafted with pH-responsive polyelectrolyte (PE) brushes. We consider the PE brushes to be modelled by our recently proposed augmented strong stretching theory (SST) model that improves the existing SST models by incorporating the effects of excluded volume interactions and an extended mass action law. Use of such augmented SST for this problem implies that this is the first study on computing i ion in PE-brush-grafted nanochannels accounting for the appropriate coupled con guration-electrostatic description of the PE brushes. i ion is obtained as functions of PE brush grafting density, medium pH and salt concentration (c ∞ ), and the density of polyelectrolyte chargeable sites (PECS). For large c ∞ , i ion increases linearly with c ∞ (as for such c ∞ , i ion becomes independent of the PE charge and is dominated by the bulk mobility and number density of the electrolyte ions), while iion is independent of c ∞ at small c ∞ (where the EDL electrostatics and the total number of ions in the system is dominated by the hydrogen ions). We further witness an enhancement of i ion for smaller pH and larger grafting density at low and moderate c ∞ , while there is little to no effect of the PECS density on the ionic current except for weakly grafted brushes at low c ∞ . We believe that this study will serve as a theoretical foundation for a large number of applications that are based on the brush-induced modification of the ionic current in a nanochannel.

42 ENGINEERING↗
DOE OSTI2021

Real-Time Omnidirectional Stereo Rendering: Generating 360° Surround-View Panoramic Images for Comfortable Immersive Viewing

Surround-view panoramic images and videos have become a popular form of media for interactive viewing on mobile devices and virtual reality headsets. Viewing such media provides a sense of immersion by allowing users to control their view direction and experience an entire environment. When using a virtual reality headset, the level of immersion can be improved by leveraging stereoscopic capabilities. Stereoscopic images are generated in pairs, one for the left eye and one for the right eye, and result in providing an important depth cue for the human visual system. For computer generated imagery, rendering proper stereo pairs is well known for a fixed view. However, it is much more difficult to create omnidirectional stereo pairs for a surround-view projection that work well when looking in any direction. One major drawback of traditional omnidirectional stereo images is that they suffer from binocular misalignment in the peripheral vision as a user's view direction approaches the zenith / nadir (north / south pole) of the projection sphere. This paper presents a real-time geometry-based approach for omnidirectional stereo rendering that fits into the standard rendering pipeline. Our approach includes tunable parameters that enable pole merging - a reduction in the stereo effect near the poles that can minimize binocular misalignment. Results from a user study indicate that pole merging reduces visual fatigue and discomfort associated with binocular misalignment without inhibiting depth perception.

360° panorama↗
DOE OSTI2020

MRDIS Case Study

The Mobile Radiation Detection and Identification System (MRDIS) is a large mobile scanner that inspects containers in transit from cargo ships for radiological materials. The MRDIS platform operates as a two-part system with one MRDIS using a plastic Polyvinyl Toleune (synthetic polymer) for primary detection and another MRDIS that uses spectroscopic detectors for secondary isotopic identification. MRDIS can operate either independently or as part of a team, depending on the needs of the port. MRDIS is controlled by a human operator, who searches the computer monitor for any traces of radiological materials when the containers pass through the center of the system. Each MRDIS can also feed data into a central system or collect data on its own for additional material analysis. The system integrates radiation detection, radioisotope identification, an optical character recognition system, occupancy/speed sensors, wireless communications, and data processing capabilities to discern what specific radiological materials are of particular interest. In addition, Sandia engineers created a detailed set of requirements for subsequent models, allowing for faster implementation of additional detection systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Kinetic Monte Carlo Simulation of Hydrogen Diffusion in Tungsten

Nuclear fusion is considered as the most promising sustainable energy source. If achieved, it could provide electricity to the mankind for millions of years. During the reaction, the fusion ash is continuously removed from the magnetic gap, the divertor region, and the divertor facing component is subjected to intense plasma bombardment. It is proposed to use tungsten as the divertor facing material, because it has low physical sputtering yield and superior thermomechanical properties. However, the high mobility of hydrogen in tungsten and the high bombardment flux bring the hydrogen isotopes deep into the tungsten tile. The presence of hydrogen in tungsten tends to weaken the gram boundaries and produce surface blistering. The ejection of tungsten particulates into the plasma core will cool the reaction and cease the fusion reactions. Therefore, it is important to have a detailed understanding of the hydrogen diffusion in tungsten bulk. The KMC method is a stochastic computer simulation to predict the time evolution of a certain system. Typically, at a given time, the system will evolve through a few possible paths with known probabilities. In each step, the KMC method analyzes the entire system and randomly determines the system evolving events based on all transition rates of all possible events and advance the physical time. This process is repeated till the simulation of the entire physical time is completed. In previous work, the authors developed a kinetic Monte Carlo (KMC) algorithm and program to simulate hydrogen diffusion process on tungsten reconstructed surface. In this article, this KMC method is extended to model the hydrogen diffusion in tungsten bulk. The diffusion coefficients are calculated and fitted to the Arrhenius equation. The result matches the experiment measurement very well. KMC diffusion simulation needs the locations of the hydrogen trapping sites, diffusion paths and the corresponding diffusion energy barriers. The hydrogen interstitial sites in tungsten crystal have been thoroughly studied by density function theory (DFT) and molecular dynamics (MD). Johnson and Carter used DFT to determine the preferred location of the hydrogen interstitial sites m tungsten crystal, which are the tetrahedral sites (T-sites) in body-centered-cubic (bcc) lattice surfaces. All T-sites are located on the surfaces of a lattice cell. There are four T-sites per surface and twelve T-sites per lattice cell. The hydrogen atoms diffuse by traveling from one T-site to one of its nearest four T-site neighbors. Thus, each T-site is surrounded by two neighbors on the same surface, and one neighbor on each of the two adjacent surfaces perpendicular to the surface holding the center T-site. The diffusion barrier between two neighboring T-sites was calculated to be 0.38 eV. Knowing the diffusion path, energy barrier, and the crystal structure, the KMC simulation is readily to be performed. Based on other researchers' DFT calculations, the hydrogen stable interstitial site in tungsten bulk is determined as the tetrahedral site on the surface of the bee lattice. Each T-site has 4 neighbors and the energy barrier between two adjacent T-sites are estimated to be 0.38 eV. Based on those facts and the KMC theory, a MATLAB program is developed to model the hydrogen diffusion in tungsten bulk. In the MATLAB program, substrate temperature, hydrogen concentration, physical time to be simulated, and the number of cycles are all customizable. To compare the KMC determined diffusion coefficients with experiment results in the literature, the simulations are performed for temperature 300 K - 2500 K and low hydrogen concentration (0.1%), mimicking the experiment condition. The calculated diffusion coefficients match the reference values measured by the experiment under low hydrogen concentration condition. The results are also fitted to the Arrhenius equation. The pre-exponential factor and the average activation energy in Arrhenius equation are obtained. The good agreement between simulation and experiment proves that the developed KMC algorithm truly reflect the well-established theory of interstitial hydrogens in tungsten. The developed program could easily be used to model the diffusion process and predict the diffusion coefficients under other concentrations and temperatures. This work is part of the ongoing development of hydrogen diffusion in tungsten integrating surface diffusion (previous work), bulk diffusion (this work), and adsorption/desorption on surface (future work)

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Enhancing radiation tolerance by controlling defect mobility and migration pathways in multicomponent single-phase alloys

A grand challenge in material science is to understand the correlation between intrinsic properties and defect dynamics. Radiation tolerant materials are in great demand for safe operation and advancement of nuclear and aerospace systems. Unlike traditional approaches that rely on microstructural and nanoscale features to mitigate radiation damage, this study demonstrates enhancement of radiation tolerance with the suppression of void formation by two orders magnitude at elevated temperatures in equiatomic single-phase concentrated solid solution alloys, and more importantly, reveals its controlling mechanism through a detailed analysis of the depth distribution of defect clusters and an atomistic computer simulation. The enhanced swelling resistance is attributed to the tailored interstitial defect cluster motion in the alloys from a long-range one-dimensional mode to a short-range three-dimensional mode, which leads to enhanced point defect recombination. Finally, the results suggest design criteria for next generation radiation tolerant structural alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Effects of Ionic Group Distribution on the Structure and Dynamics of Amorphous Polymer Melts

Ionizable groups tethered to a polymer backbone often associate to form ionic clusters, whose features are determined by the balance of the polymer backbone and electrostatics. These assemblies impact the dynamics of the macromolecules and their ability to transport ions. Here, using fully atomistic molecular dynamics (MD) simulations, we investigate the effects of the distribution of ionizable groups along the polymer backbone on cluster characteristics and the resulting impacts on the structure and dynamics of amorphous polymers. Particularly, we probe polystyrene sulfonates (PSS) with random, precise, and block configurations of the SO 3 – sulfonate groups along the backbone with Na + as the counterion. We find that the distribution of the ionic groups affects the shape and distribution of the clusters as well as the internal packing of the ionizable groups in the cluster and the number of unique chains that participate in each cluster, affecting the structure and the dynamics of the polymers. Furthermore, the signature of ionic clusters, observed in the static structure factor S(q) for all three distributions, is significantly more pronounced for the precise and blocky polymers compared to the random one. Remarkably, we find that the local mobility of the polymer segments is not only affected by the number and size of the clusters but also by the number of polymer chains associated with clusters.

36 MATERIALS SCIENCE↗
DOE OSTI2015

SU-E-T-437: Four-Dimensional Treatment Planning for Lung VMAT-SBRT

Purpose: To assess optimal treatment planning approach of Volumetric Modulated Arc Therapy for lung Stereotactic Body Radiation Therapy (VMAT-SBRT). Methods: Subjects were 10 patients with lung cancer who had undergone 4DCT. The internal target volume (ITV) volume ranged from 2.6 to 16.5cm{sup 3} and the tumor motion ranged from 0 to 2cm. From 4DCT, which was binned into 10 respiratory phases, 4 image data sets were created; maximum intensity projection (MIP), average intensity projection (AIP), AIP with the ITV replaced by 0HU (RITV-AIP) and RITV-AIP with the planning target volume (PTV) minus the internal target volume was set to −200 HU (HR-AIP). VMAT-SBRT plans were generated on each image set for a patient. 48Gy was prescribed to 95% of PTV. The plans were recalculated on all phase images of 4DCT and the dose distributions were accumulated using a deformable image registration software MIM Maestro™ as the 4D calculated dose to the gross tumor volume (GTV). The planned dose to the ITV and 4D calculated dose to the GTV were compared. Results: In AIP plan, 10 patients average of all dose parameters (D1%, D-mean, and D99%) discrepancy were 1Gy or smaller. MIP and RITV-AIP plans resulted in having common tendency and larger discrepancy than AIP plan. The 4D dose was lower than the planned dose, and 10 patients average of all dose parameters discrepancy were in range 1.3 to 2.6Gy. HR-AIP plan had the largest discrepancy in our trials. 4D calculated D1%, D-mean, and D99% were resulted in 3.0, 4.1, and 6.1Gy lower than the expected in plan, respectively. Conclusion: For all patients, the dose parameters expected in AIP plan approximated to 4D calculated. Using AIP image set seems optimal treatment planning approach of VMAT-SBRT for a mobile tumor. Funding Support: This work was supported by the Japan Society for the Promotion of Science Core-to-Core program (No. 23003)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Laparoscopic Isolated Total Caudate Lobectomy for Hepatocellular Carcinoma Located in the Paracaval Portion of the Cirrhotic Liver

Background: Despite the widespread use of laparoscopic hepatectomies in past decades, laparoscopic isolated total caudate lobectomy for hepatocellular carcinoma (HCC) remains challenging,{sup 1,2} especially for patients with cirrhosis. Moreover, a laparoscopic isolated total caudate lobectomy for HCC originating in the paracaval portion of the caudate lobe is very rare. We herein present a video showing laparoscopic total caudate lobectomy for a cirrhotic patient with HCC located in the paracaval portion of the caudate lobe. Methods: A 58-year-old woman who suffered from hepatitis C virus-related cirrhosis was admitted to our institution. The preoperative computed tomography showed a 2.5 × 2.0 cm liver mass located in segment I that was very close to the right hepatic pedicle. Although her liver function was Child–Pugh A, the indocyanine green (ICG)-15 test was high at 10.9%. Right hepatectomy plus caudate lobectomy was not adopted because of the severe cirrhosis and the elevated ICG-15. Thus, laparoscopic isolated total caudate lobectomy was contemplated. Results: The patient was placed in the supine position. After full mobilization, the caudate lobe was exposed. The third porta of the liver was then dissected and the short hepatic veins were controlled with clips and LigaSure. The dissection was finished when the whole third porta of the liver was freed. Subsequently, the portal branches to the caudate lobe were ligated and cut. The combination between the left- and right-sided laparoscopic approaches was used to transect liver parenchyma. The superficial parenchyma was divided using an harmonic scalpel, while the deeper tissue was divided using a Cavitron ultrasonic aspirator (CUSA). The Pringle maneuver was used intermittently during the parenchymal transection as necessary. In the left-sided approach, the caudate lobe was resected along the left and middle hepatic vein toward the right side, to expose the dorsal semicircle of the right hepatic vein. In the right-sided approach, the resection started from the right border of the process portion to the root of the right hepatic vein in the cranial direction. Finally, the whole caudate lobe was resected and the three main hepatic veins were exposed on the cutting plane. The specimen was removed from suprapubic incision. The operative time was 300 min and the total Pringle time was 50 min. The postoperative course was uneventful. Conclusions: A laparoscopic isolated total caudate lobectomy for HCC located in the paracaval portion of the cirrhotic liver seems to be feasible and safe in selected patients.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Uranium(VI) Sorption onto Montmorillonite Clay in the Presence of Ca2+/Calcite Impurities

The storage of nuclear waste creates a series of significant environmental risks. One attempt to minimize these potential impacts is the use of underground geological repositories, where waste containers are surrounded by geologic buffer materials creating an engineered barrier. One buffer material that has been of interest is bentonite, which is largely composed of montmorillonite clay. These barriers limit the mobility of radioactive contaminants, such as uranium(VI), into environmental systems based on contaminant sorption onto the clay material. System conditions, such as pH, the presence of mineral impurities such as calcite, and the concentrations of U(VI) and atmospheric CO2 also affect the sorption behavior of U(VI) onto these clay barriers. This study focuses on the effects of Ca2+ and calcite (CaCO3), a common impurity found in montmorillonite on the sorption behavior of U(VI). Computer simulations of the chemical solution species (chemical form) of U(VI), in the absence and presence of Ca2+/calcite impurities are performed in parallel with laboratory sorption experiments. Experimental data will be compared to modeling results to help obtain further insights regarding the impacts of Ca2+/calcite impurities on U(VI) solution speciation and sorption behavior onto montmorillonite.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Molecular Dynamics Study of the Effect of Grafting Density on Ion Diffusivity in a MARTINI Coarse-Grained Strong Polyelectrolyte Brush

Because surface-grafted polyelectrolyte brushes (PEBs) are responsive to external stimuli, such as electric fields and ionic strength, PEBs are attractive for applications ranging from drug delivery to separation technologies. Essential to PEB utilization is understanding how critical parameters like grafting density (σ) impact the PEB structure and the dynamics of the PEB and counterions. To study the effect of σ on PEB and the counterion structure and dynamics, we fine-tune a coarse-grained model that retains the chemical specificity of a strong polyelectrolyte, poly[(2-(methacryloyloxy)ethyl) trimethylammonium chloride] (PMETAC), using the MARTINI force field. Using “salt-free” conditions where the counterion concentration balances the charge on the brush, we build coarse-grained (CG) molecular dynamics simulations for MARTINI PMETAC brushes (N = 150 monomers; M W = 31.2 kg/mol) at experimentally relevant values of σ = 0.05, 0.10, 0.20, and 0.40 chains/nm 2 . Using 5 μs simulations, we investigate the effects of grafting density on the PEB structure, ion dissociation dynamics, polymer mobility, and counterion diffusivity. Results show that competition between electrostatic interactions, steric hindrance, and polymer mobility controls counterion diffusivity. Finally, the interplay of these factors leads to diffusivity that depends non-monotonically on σ, with counterion diffusivity peaking at an intermediate σ = 0.10 chains/nm 2 .

36 MATERIALS SCIENCE↗
DOE OSTI2020

GEMINI Case Study

Sandia's GEMINI-Scout Mine Rescue Robot is an unmanned ground vehicle designed to enter potentially hazardous environments to explore, assess, and evaluate dangerous situations first responders may face when conducting a rescue mission. GEMINI is approximately four feet long and two feet tall, which enables the robot to maneuver through small locations on rough terrains caused by earthquakes, fires, or radiological incidents. GEMINI uses track propulsion to climb stairs, travel through gravel and sand pits, pivot in place, and traverse 45-degree climbs with few problems. Furthermore, the vehicle's dual tracked-chassis design allows it to operate in hostile, dark, muddy, high-temperature, and explosive debris-strewn environments, while maintaining efficient ground mobility. The mobility and modularity of the vehicle allow for easy integration of sensors to conduct gas and temperature sensing and offers pan/tilt, zoom color, and thermal camera video streaming capabilities. The vehicle is also able to carry a payload of about 50 pounds of batteries and can handle an additional 200 pounds of payload, whether for additional diagnostics, supplies, or clothing for those trapped in an effected area. GEMINI is remotely operated through a wireless connection and an onboard computer running a customized embedded control application, which directly communicates to all onboard components except for the audio and video systems. When line of sight is not possible, operators use a shockresistant fiber optic cable to ensure continuous functionality of the vehicle. This allows for direct local control of the vehicle, which streams collected data back to the operator for enhanced situational awareness. In addition, the vehicle incorporates safety features such as explosion proof housing to ensure safe electronic operations in hazardous gas or flooded environments; a four-channel video link and two-way audio to ensure located survivors can communicate with operators; and an MSHA-approved multi-gas sensor to monitor air quality.

42 ENGINEERING↗
DOE OSTI2022

Findings on Subtask 3.1 - Bakken Rich Gas Enhanced Oil Recovery Project

Total in-place oil for the Bakken petroleum system (BPS) (which includes the Bakken and Three Forks Formations) has been estimated to be 600 billion barrels (bbl). However, BPS wells have decline rates as high as 85% over the first 3 years of their lives, and primary recovery factors typically range from 3% to 10% of original oil in place. Given the low initial recovery rates, even small incremental productivity improvements could dramatically increase technically recoverable oil in the BPS. One potential solution is enhanced oil recovery (EOR) using gas injection, such as carbon dioxide (CO2) or hydrocarbon (HC) gases. While commonly used in conventional reservoirs, CO2 EOR in unconventional tight oil reservoirs has been limited to pilot tests. EOR using rich gas (mixture of methane, ethane, and propane) has also been employed in numerous pilots in several unconventional plays and has recently been successfully applied in the Eagle Ford play. If successful, large-scale gas-based EOR in the BPS could dramatically increase oil productivity and recovery factors and extend the life of the play for decades. While CO2 may be a technically suitable working fluid for EOR in the BPS, supplies are limited and costs for using CO2 in EOR pilots are prohibitively high. Meanwhile, produced gas flaring has presented challenges for BPS operators in North Dakota. Analysis conducted by the North Dakota Pipeline Authority indicates that the current gas-gathering infrastructure in North Dakota is insufficient to accommodate all of the associated gas that is produced from the BPS. The geographically isolated location of North Dakota relative to large natural gas markets, combined with suppressed natural gas prices, has made it economically challenging for industry to invest capital in expanding gas-gathering infrastructure in the state. These circumstances led to a research program conducted by the Energy & Environmental Research Center (EERC) in partnership with Liberty Resources Management Company LLC (LR) to examine the potential to use rich gas injection for EOR and mitigate flaring. A rich gas EOR pilot test was designed and executed by LR at its Stomping Horse development area in Williams County, North Dakota. From July 2018 through May 2019, a total of 160 million standard cubic feet (MMscf) of rich produced gas was injected into the BPS using five different wells in a sequential injection strategy. LR’s Leon–Gohrick drill spacing unit (DSU) was used as the test site. Regulatory oversight was provided by the North Dakota Industrial Commission (NDIC). Technical support was provided by the EERC through a series of laboratory, modeling, and field-based activities, and additional post-pilot research activities incorporated learnings from the test, developed new laboratory data, improved fracture modeling methods, and developed machine learning and big data analytics. The results from the Stomping Horse rich gas EOR pilot activities indicate that developing an effective, economical EOR approach for the BPS will require more field tests. Another key lesson learned from the Stomping Horse tests is that detailed pre- and posttest data on reservoir conditions and fluids production are essential. Robust reservoir characterization provides information that is crucial to creating realistic geomodels and conducting valid dynamic simulations of potential EOR scenarios. A detailed understanding of the completions and production history of offset wells is also necessary for valid test result interpretations. This knowledge is essential to designing the operational parameters of injectivity tests and interpreting the results. A conformance control strategy is also essential to success. Laboratory-based examinations of rich gas interactions with reservoir fluids and rocks were conducted, with an emphasis on determining the ability to mobilize oil in the tight reservoir rocks and shales of the BPS. Injection fluid composition was shown to have a positive impact on reducing reservoir oil minimum miscibility pressure (MMP), reducing interfacial tension (IFT), and altering wettability. IFT and contact angle measurements demonstrated that wettability can be altered in the presence of rich gas, suggesting the potential to improve oil recovery. Iterative modeling of surface infrastructure and reservoir performance using data generated by the various project activities was conducted. A geologic model of the Stomping Horse area was built; history-matched oil, gas, and water production was used in simulations of various EOR scenarios. Early programmatic modeling results were used to support LR’s design and operation of the EOR pilot and to provide insight regarding optimization of future commercial-scale BPS EOR design and operations. Post-pilot modeling focused on alternative methods of understanding complex fracture networks and accelerating simulation time. These led to improved simulation run times and provide excellent history-matching results. Several of these iterative models were used as the bases for developing algorithms into machine learning and big data analytics. History matching in reservoir simulation is time-consuming and computer processing-intensive. Machine learning algorithms were created, and an automated history-matching tool was developed. A large set of synthetic reservoir simulations were created to generate well responses (oil, gas, and water production, well bottomhole pressure [BHP], and tracer or propane breakthrough) for a set of EOR operating parameters that included offset well status (open or closed), injectate (rich gas or propane), injection rate, and injection well BHP. A user interface was developed to provide real-time visualization. Machine learning-based models were developed to provide rapid forecasting of well performance given a set of user-defined EOR operating parameters. These predictive models allow the user to modify the offset well status, injection rate, and injection well BHP and rapidly forecast future production performance. The combination of real-time visualization tools with real-time forecasting tools provides a framework for real-time control—operational changes that the EOR site operator can enact (e.g., changing gas injection rates) to affect the observed performance and potentially improve the EOR outcome. There is great reason to be optimistic about the future of EOR in the Bakken. The results of the laboratory studies suggest significant potential for high rates of oil mobilization using produced field gas injection under the right conditions. The results of the lab studies, combined with rigorous statistical analysis of well production data and associated modeling efforts, confirm the notion that fluid mobility within the reservoir is controlled by fractures. As more knowledge is gained about the nature and distribution of fracture networks in the Bakken, the industry will be in a better position to predict and, ultimately, influence fluid mobility. New field tests are necessary to develop a more complete understanding of those conditions. Thoughtful and creatively engineered field tests within a well-characterized geologic setting will yield the fundamental knowledge needed to take Bakken oil production to the next level. This subtask was cofunded through the EERC–U.S. Department of Energy Joint Program on Research and Development for Fossil Energy-Related Resources Cooperative Agreement No. DE-FE0024233. Nonfederal funding was provided by the North Dakota Industrial Commission’s Oil and Gas Research Program and Computer Modelling Group.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2017

Novel Analysis and Visualization of Chemical Events for Public Health Surveillance

Pacific Northwest National Laboratory hosted an intern-based web application development contest in the summer of 2016 centered around developing novel chemical surveillance applications to aid in health situational awareness. Making up the three teams were three graduate students (n=9) from various US schools majoring in non-public health domains, such as computer science and user design. The interns successfully developed three applications that demonstrated a value-add to chemical surveillance—ChemAnalyzer (text analytics), RetroSpect (retrospective analysis of chemical events),and ToxicBusters (geo-based trend analytics). These applications will be the basis for the first chemical surveillance application to be incorporated into the DTRA Biosurveillance Ecosystem (BSVE).Pacific Northwest National Laboratory (PNNL), on behalf the Defense Threat Reduction Agency (DTRA; project number CB10190), hosts an annual intern- based web app development contest. Previous competitions have focused on mobile biosurveillance. The 2016 competition pivoted away from biosurveillance to focus on addressing challenges within the field of chemical surveillance and increasing public health chemical situational awareness. The result of the app will be integrated within the DTRA BSVE. PNNL hosted nine graduate interns for a 10-week period in the summer of 2016 as participants in a summer web application development contest. Students were drawn from such fields as software engineering and user experience and design and placed into three teams of three students. The challenge presented to the interns was to design and develop a fully-functional web application that would address a critical need within the chemical surveillance community. The interns developed their own ideas (vetted by PNNL and DTRA), discovered and integrated their own data sources, and produced their own visualizations and analytics, independent of any assistance outside of that provided in an advisory capacity. The competition end with a judging event with a panel of subject matter experts and cash awards were distributed to the teams. Each team produced a unique application. Although there was mild overlap between some of the ideas, the applications were developed independently and each reflected the unique contributions of the teams. ChemAnalyzer is a text-analytics platform designed to facilitate more data-driven decision, given a corpus of text data about a chemical event. Their platform provided the ability to automatically identify and highlight key words in documents related to chemical events. The keywords are drawn from an ontology installed with the system, as well as any user-identified keywords. The ChemAnalyzer team finished in third place. The RetroSpect team developed a visual analytic tool for performing retrospective analysis and monitoring of chemical events. Their app provided the ability to search and analyze past events, as well as visualization of state and county information for the recorded chemical events. The RetroSpect team finished in second place. The Toxic busters team - the winners of the competition - created a geo-based situational awareness tool for tracking chemical events. Their app featured an updateable map overlay, search functionality for finding specific or related events, incident and city/state/national-level statistics and trends, as well as news and social media integration based on keywords related to chemical surveillance. Each of the apps developed by the teams provides value to an analyst tasked with monitoring chemical events. The apps integrated unique data sources to provides a full picture of a chemical event, and its effects upon the surrounding population. This integrated analytics provides a valuable benefit over existing workflows, where analysts must monitor news, social, and other information sources manually for real-time information. The apps developed by these interns are designed to enable identification and analysis of the incident as quickly as possible, allowing for more timely assessments of the incident and its impacts. The web app development contest provided a unique opportunity for students to learn about the emerging needs in chemical surveillance as it relates to health situational awareness. Students were drawn from a variety of fields and were tasked with developing novel web apps addressing some of the most pressing challenges in the field of chemical surveillance. The ideas generated by the students will help form the basis for future chemical surveillance application development to be integrated with the DTRABSVE.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Forecasting influenza activity using machine-learned mobility map

Human mobility is a primary driver of infectious disease spread. However, existing data is limited in availability, coverage, granularity, and timeliness. Data-driven forecasts of disease dynamics are crucial for decision-making by health officials and private citizens alike. In this work, we focus on a machine-learned anonymized mobility map (hereon referred to as AMM) aggregated over hundreds of millions of smartphones and evaluate its utility in forecasting epidemics. We factor AMM into a metapopulation model to retrospectively forecast influenza in the USA and Australia. We show that the AMM model performs on-par with those based on commuter surveys, which are sparsely available and expensive. We also compare it with gravity and radiation based models of mobility, and find that the radiation model’s performance is quite similar to AMM and commuter flows. Additionally, we demonstrate our model’s ability to predict disease spread even across state boundaries. Our work contributes towards developing timely infectious disease forecasting at a global scale using human mobility datasets expanding their applications in the area of infectious disease epidemiology.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Virtual machine-based simulation platform for mobile ad-hoc network-based cyber infrastructure

In modeling and simulating complex systems such as mobile ad-hoc networks (MANETs) in de-fense communications, it is a major challenge to reconcile multiple important considerations: the rapidity of unavoidable changes to the software (network layers and applications), the difficulty of modeling the critical, implementation-dependent behavioral effects, the need to sustain larger scale scenarios, and the desire for faster simulations. Here we present our approach in success-fully reconciling them using a virtual time-synchronized virtual machine(VM)-based parallel ex-ecution framework that accurately lifts both the devices as well as the network communications to a virtual time plane while retaining full fidelity. At the core of our framework is a scheduling engine that operates at the level of a hypervisor scheduler, offering a unique ability to execute multi-core guest nodes over multi-core host nodes in an accurate, virtual time-synchronized manner. In contrast to other related approaches that suffer from either speed or accuracy issues, our framework provides MANET node-wise scalability, high fidelity of software behaviors, and time-ordering accuracy. The design and development of this framework is presented, and an ac-tual implementation based on the widely used Xen hypervisor system is described. Benchmarks with synthetic and actual applications are used to identify the benefits of our approach. The time inaccuracy of traditional emulation methods is demonstrated, in comparison with the accurate execution of our framework verified by theoretically correct results expected from analytical models of the same scenarios. In the largest high fidelity tests, we are able to perform virtual time-synchronized simulation of 64-node VM-based full-stack, actual software behaviors of MANETs containing a mix of static and mobile (unmanned airborne vehicle) nodes, hosted on a 32-core host, with full fidelity of unmodified ad-hoc routing protocols, unmodified application executables, and user-controllable physical layer effects including inter-device wireless signal strength, reachability, and connectivity.

97 MATHEMATICS AND COMPUTING↗