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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
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 OSTI2013

Dynamic electrophoretic fingerprinting of the HIV-1 envelope glycoprotein

Background: Interactions between the HIV-1 envelope glycoprotein (Env) and its primary receptor CD4 are influenced by the physiological setting in which these events take place. In this study, we explored the surface chemistry of HIV-1 Env constructs at a range of pH and salinities relevant to mucosal and systemic compartments through electrophoretic mobility (EM) measurements. Sexual transmission events provide a more acidic environment for HIV-1 compared to dissemination and spread of infection occurring in blood or lymph node. We hypothesize functional, trimeric Env behaves differently than monomeric forms. Results: The dynamic electrophoretic fingerprint of trimeric gp140 revealed a change in EM from strongly negative to strongly positive as pH increased from that of the lower female genital tract (pHx) to that of the blood (pHy). Similar findings were observed using a trimeric influenza Haemagglutinin (HA) glycoprotein, indicating that this may be a general attribute of trimeric viral envelope glycoproteins. These findings were supported by computationally modeling the surface charge of various gp120 and HA crystal structures. To identify the behavior of the infectious agent and its target cells, EM measurements were made on purified whole HIV-1 virions and primary T-lymphocytes. Viral particles had a largely negative surface charge, and lacked the regions of positivity near neutral pH that were observed with trimeric Env. T cells changed their surface chemistry as a function of activation state, becoming more negative over a wider range of pH after activation. Soluble recombinant CD4 (sCD4) was found to be positively charged under a wide range of conditions. Binding studies between sCD4 and gp140 show that the affinity of CD4-gp140 interactions depends on pH. Conclusions: Taken together, these findings allow a more complete model of the electrochemical forces involved in HIV-1 Env functionality. These results indicate that the influence of the localized environment on the interactions of HIV with target cells are more pronounced than previously appreciated. There is differential chemistry of trimeric, but not monomeric, Env under conditions which mimic the mucosa compared to those found systemically. This should be taken into consideration during design of immunogens which targets virus at mucosal portals of entry.

59 BASIC BIOLOGICAL SCIENCES↗
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↗
DOE OSTI2012

Migration of point defects and a defect pair in zinc oxide using the dimer method

The migration mechanism and the minimum energy path of vacancies, interstitials and an interstitial-vacancy pair in zinc oxide have been studied by the dimer method. The in-plane and out-of-plane migrations of zinc and oxygen vacancies are found to be anisotropic. The kick-out mechanism is energetically preferred to zinc and oxygen interstitials that can easily migrate through the ZnO crystal lattice. In addition, the migration process of an interstitial-vacancy pair as a complex of an octahedral oxygen interstitial and a zinc vacancy is dominated by an oxygen interstitial/zinc vacancy successive migration. The energy barriers indicate that the existence of oxygen interstitial in the defect pair can promote the mobility of zinc vacancy, whereas the migration of oxygen interstitial is slowed down due to the presence of zinc vacancy. In the end, we show a possible migration path of the interstitial-vacancy pair that can be dissociated through a set of displacement movements.

Computer simulations↗
DOE OSTI2012

Multi-Timescale Investigation of Radiation Damage near TiO2 Rutile Grain Boundaries

Although grain boundaries (GBs) have been experimentally demonstrated to serve as sinks for absorbing radiation induced defects and improving the radiation tolerance of materials, the detailed atomistic interactions between defects and GBs leading to this enhanced tolerance are not well understood. In oxide ceramics the interactions are further complicated as defects can be charged and grain boundaries may exhibit space charge and charge dipole effects. Here, we use two atomistic modeling methods to examine the role of GBs in a model oxide system, rutile TiO2, in modifying defect production during irradiation events. The GB studied is a symmetric tilt GB with a rotation axis of [100] and a rotation angle of 15.25{sup o}. We use molecular dynamics to investigate defect production near the GB at both 300K and 1000 K and find that the damage production is sensitive to the initial distance of the primary knock-on atom (PKA) from the GB. We find three distinct regimes in which GBs have different effects on modifying defect production. Similar to GBs in metals, the GB absorbs more interstitials than vacancies at certain distances while this behavior of biased loading of interstitials diminishes at other distances. Further, we obtain the statistics of both interstitial and vacancy clusters 2 produced in collision cascades in terms of their compositions at two temperatures. We find that perfectly stoichiometric defect clusters (Schottky and anti-Schottky clusters) represent a small fraction of the total defect clusters produced. Moreover, a significant reduction in the number of interstitial clusters at 1000 K compared to 300 K is thought to be a consequence of enhanced migration of interstitials towards the GB. Finally the kinetic properties of certain defect clusters are investigated with temperature accelerated dynamics, without any priori assumptions of migration mechanisms. We find that small interstitial clusters become mobile at high temperatures while small vacancy clusters do not. Multiple migration pathways exist and are typically complex and non-intuitive. We use this kinetic information to explain experimental observations and predict their long-time migration behavior near GBs.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Raman and electrical transport properties of few-layered arsenic-doped black phosphorus

Black phosphorus (b-P) is an allotrope of phosphorus whose properties have attracted great attention. In contrast to other 2D compounds, or pristine b-P, the properties of b-P alloys have yet to be explored. In this report, we present a detailed study on the Raman spectra and on the temperature dependence of the electrical transport properties of As-doped black phosphorus (b-AsP) for an As fraction x = 0.25. The observed complex Raman spectra were interpreted with the support of Density Functional Theory (DFT) calculations since each original mode splits in three due to P–P, P–As, and As–As bonds. Field-effect transistors (FET) fabricated from few-layered b-AsP exfoliated onto Si/SiO 2 substrates exhibit hole-doped like conduction with a room temperature ON/OFF current ratio of ~10 3 and an intrinsic field-effect mobility approaching ~300 cm 2 V -1 s -1 at 300 K which increases up to 600 cm2 V-1 s-1 at 100 K when measured via a 4-terminal method. Remarkably, these values are comparable to, or higher, than those initially reported for pristine b-P, indicating that this level of As doping is not detrimental to its transport properties. The ON to OFF current ratio is observed to increase up to 10 5 at 4 K. At high gate voltages b-AsP displays metallic behavior with the resistivity decreasing with decreasing temperature and saturating below T ~100 K, indicating a gate-induced insulator to metal transition. Similarly to pristine b-P, its transport properties reveal a high anisotropy between armchair (AC) and zig-zag (ZZ) directions. Electronic band structure computed through periodic dispersion-corrected hybrid Density Functional Theory (DFT) indicate close proximity between the Fermi level and the top of the valence band(s) thus explaining its hole doped character. Finally, our study shows that b-AsP has potential for optoelectronics applications that benefit from its anisotropic character and the ability to tune its band gap as a function of the number of layers and As content.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Real-time control of connected vehicles in signalized corridors using pseudospectral convex optimization

Recent advances in Connected and Automated Vehicle (CAV) technologies have opened up new opportunities to enable safe, efficient, and sustainable transportation systems. However, developing reliable and rapid speed control algorithms in highly dynamic environments with complex inter-vehicle interactions and nonlinear vehicle dynamics is still a daunting task. In this paper, we develop a novel speed control method for CAVs to produce optimal speed profiles that minimize the fuel consumption and avoid idling at signalized intersections. To this end, an optimal control problem is formulated using the information of the upcoming traffic signal to adapt vehicles' speeds to avoid frequent stop-and-go driving patterns. Here, by applying the pseudospectral discretization method and the sequential convex programming method, the computational efficiency is greatly improved, enabling potential real-time on-vehicle applications. In addition, the algorithm is implemented under a model predictive control framework to ensure online control with instant response for collision avoidance and robust vehicle coordination. The proposed algorithm is verified through numerical simulations of three different traffic scenarios. The convergence and accuracy of the proposed approach are demonstrated by comparing with a popular nonlinear solver. Furthermore, the benefit of the proposed method in both traffic mobility and fuel efficiency is validated using the speed profile determined from a traffic following model in a simulation software as the baseline.

42 ENGINEERING↗
DOE OSTI2023

Systemwide Planning with a Branch-and-Price Algorithm for Pavement-Marking Assessment Data Collection via the Mobile Retroreflectivity Unit Routing Model

The visibility of pavement markings is one of the most critical factors for traffic safety, and a periodical assessment plan is crucial for maintaining this function. Traditional assessment methods, such as visual windshield surveys or manual testing using handheld devices, are unsafe, time-consuming, and labor-intensive. In recent years, transportation agencies have begun to adopt the use of mobile retroreflectivity units (MRUs) for condition assessment of pavement markings. MRUs, different from other manual methods, can be utilized to collect large-scale retroreflectivity data in an efficient manner. However, no relevant research has yet proposed a mathematical optimization model for arranging the evaluation schedule and paths of MRUs. This study aims to propose a MRU routing model, and an efficient solution methodology. A branch-and-price algorithm, including column generation and branch-and-bound, was implemented. Computational experiments have been conducted based on actual tasks from the Florida MRU program for validation. In conclusion, results show that the proposed solution methodology with a set partitioning model in this study not only finds the optimal solution for problems with tasks less than 60, but also effectively narrows the solution gap to be within 1.0% for problems with tasks less than 131.

42 ENGINEERING↗
DOE OSTI2025

Growth-induced Donnan exclusion influences swelling kinetics in highly charged dynamic polymerization hydrogels

Polymeric gels crosslinked by DNA sequences can exploit DNA strand-displacement reactions to promote swelling through dynamic polymerization. The degree of swelling and the rate of swelling must be directly tunable to achieve the promise of programmable soft matter. Though the kinetics of the strand-displacement reaction provide insertion rates up to 10 4 /Molar/second as measured in bulk solution, DNA hydrogel swelling can take upwards of 30 h to complete. Computational modeling of the reaction-induced swelling of these gels with our recently-developed reactive electrochemomechanical theory (Zimmerman et al., 2024) suggests that their extraordinarily slow swelling is partly due to a scaling mismatch between the addition of charge and the addition of fluid volume, leading to a large transient increase in the fixed charge density. The significant increase in the gel’s fixed charge density, due to the binding of negatively charged DNA, sharply restricts the concentration of mobile hairpins through the phenomenon of Donnan charge exclusion, an effect commonly exploited in nanofiltration applications using polymeric membranes. The scaling problem is overcome when the mean additional swelling provided to the hydrogel by addition of a crosslink is above a critical value, thus the swelling outpaces the charge accumulation, leading the fixed charge density to drop and significantly accelerating the swelling process. This study shows that Donnan exclusion can explain the kinetics of DNA hydrogel swelling, and studies ways to modulate the reaction speed by either modifying the salt concentration or increasing or decreasing the number of base pairs in each DNA sequence.

42 ENGINEERING↗
DOE OSTI2015

Multi-qubit gates protected by adiabaticity and dynamical decoupling applicable to donor qubits in silicon

In this paper, we present a strategy for producing multiqubit gates that promise high fidelity with minimal tuning requirements. Our strategy combines gap protection from the adiabatic theorem with dynamical decoupling in a complementary manner. Energy-level transition errors are protected by adiabaticity and remaining phase errors are mitigated via dynamical decoupling. This is a powerful way to divide and conquer the various error channels. In order to accomplish this without violating a no-go theorem regarding black-box dynamically corrected gates [Phys. Rev. A 80, 032314 (2009)], we require a robust operating point (sweet spot) in control space where the qubits interact with little sensitivity to noise. There are also energy gap requirements for effective adiabaticity. We apply our strategy to an architecture in Si with P donors where we assume we can shuttle electrons between different donors. Electron spins act as mobile ancillary qubits and P nuclear spins act as long-lived data qubits. Furthermore, this system can have a very robust operating point where the electron spin is bound to a donor in the quadratic Stark shift regime. High fidelity single qubit gates may be performed using well-established global magnetic resonance pulse sequences. Single electron-spin preparation and measurement has also been demonstrated. Thus, putting this all together, we present a robust universal gate set for quantum computation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

SU-E-J-115: Correlation of Displacement Vector Fields Calculated by Deformable Image Registration Algorithms with Motion Parameters of CT Images with Well-Defined Targets and Controlled-Motion

Purpose: To investigate correlation of displacement vector fields (DVF) calculated by deformable image registration algorithms with motion parameters in helical axial and cone-beam CT images with motion artifacts. Methods: A mobile thorax phantom with well-known targets with different sizes that were made from water-equivalent material and inserted in foam to simulate lung lesions. The thorax phantom was imaged with helical, axial and cone-beam CT. The phantom was moved with a cyclic motion with different motion amplitudes and frequencies along the superior-inferior direction. Different deformable image registration algorithms including demons, fast demons, Horn-Shunck and iterative-optical-flow from the DIRART software were used to deform CT images for the phantom with different motion patterns. The CT images of the mobile phantom were deformed to CT images of the stationary phantom. Results: The values of displacement vectors calculated by deformable image registration algorithm correlated strongly with motion amplitude where large displacement vectors were calculated for CT images with large motion amplitudes. For example, the maximal displacement vectors were nearly equal to the motion amplitudes (5mm, 10mm or 20mm) at interfaces between the mobile targets lung tissue, while the minimal displacement vectors were nearly equal to negative the motion amplitudes. The maximal and minimal displacement vectors matched with edges of the blurred targets along the Z-axis (motion-direction), while DVF’s were small in the other directions. This indicates that the blurred edges by phantom motion were shifted largely to match with the actual target edge. These shifts were nearly equal to the motion amplitude. Conclusions: The DVF from deformable-image registration algorithms correlated well with motion amplitude of well-defined mobile targets. This can be used to extract motion parameters such as amplitude. However, as motion amplitudes increased, image artifacts increased significantly and that limited image quality and poor correlation between the motion amplitude and DVF was obtained.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

How mixing tetraglyme with the ionic liquid 1- n -hexyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide changes volumetric and transport properties: An experimental and computational study

The viscosity and density of the ionic liquid (IL) 1-n-hexyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([C 6 mim][NTf 2 ]), the molecular solvent tetraethylene glycol dimethyl ether (tetraglyme or G4) and their binary mixtures were measured experimentally as a function of temperature. The same systems were also studied using classical molecular dynamics (MD) simulations. The viscosities of the [C 6 mim][NTf 2 ]/G4 mixtures decrease with increasing G4 concentration, though not as much as an ideal mixing model would predict. Detailed analysis of the MD results reveals that G4 preferentially solvates cations, leading to a reduction in the interaction energy between cations and anions and a subsequent enhancement in anion mobility. A similar effect has been reported when glymes are mixed with salts containing alkali metal cations, with the resulting mixtures being called “solvate” ionic liquids. The simulations predict that the ionic conductivity will be maximized when the G4 mole fraction is around 10–20%. The ability of G4 to effectively solvate the cations stems from localized charges on the oxygen. In conclusion, the simulations predict that solvents having large localized positive charges would preferentially solvate anions, leading to enhanced cation mobility.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗