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At least 559 records · Page 31

Building the Traffic, Navigation, and Situation Awareness System (T-NASA) for Surface Operations

We report the results of a part-task simulation evaluating the separate and combined effects of an electronic moving map display and newly developed HUD symbology on ground taxi performance, under moderate- and low-visibility conditions. Twenty-four commercial airline pilots carried out a series of 28 gate-to-runway taxi trials at Chicago O'Hare. Half of the trials were conducted under moderate visibility (RVR 1400 ft), and half under low visibility (RVR 700 ft). In the baseline condition, where navigation support was limited to surface features and a Jeppesen paper map, navigation errors were committed on almost half of the trials. These errors were virtually abolished when the electronic moving map or the HUD symbology was available; in addition, compare, the baseline condition, both forms of navigation aid yielded an increase in forward taxi speed. The speed increase was greater for HUD than the electronic moving map, and greater under low visibility than under moderate visibility. These results suggest that combination of electronic moving map and HUD symbology has the potential to greatly increase the efficiency of ground operations, particularly under low-visibility conditions.

McCann, Robert S.↗

Smart Ventilation for Advanced California Homes

This project investigated smart ventilation approaches to minimize energy use for providing indoor air quality (IAQ) in high performance new California homes. Evaluation criteria included annual ventilation-related energy, peak energy and time-of-use savings, and the indoor air quality relative to a minimally code-compliant ventilation system. The simulations used CONTAM’s air flow and contaminant transport model, combined with the EnergyPlus building loads model. House types representing the default California Energy Code compliance homes were investigated for four California climate zones, covering a wide range of climate types. Both single and multi-zone smart ventilation controls were investigated. Contaminant sources included contaminants emitted continuously and varying with time, temperature and relative humidity, episodic emissions from occupant activities and outdoor particles. Single-zone ventilation controls that varied ventilation depending on outdoor temperatures were able to consistently save half of ventilation-related energy without compromising long-term IAQ. Ventilation strategies that tracked occupancy were less successful, because this work included generic contaminants with constant background emission rates. Energy performance for occupancy controls improved with a one-hour pre-occupancy flush out strategy. The addition of zoning ventilation controls did not offer significant IAQ to energy improvements compared to non-zonal versions of the same ventilation system type. The best controls had HVAC energy savings of 10-20%, with individual cases reaching up to 40% savings. However, these savings cannot be achieved without worsening personal exposures for at least one contaminant. A metric is needed to assess the competing changes in exposure to different contaminants in order to determine the net-health impacts of a control strategy. Controls that directly sensed contaminants and controlled them to acceptable levels showed that the California OEHHA limit for formaldehyde completely dominates system performance, with homes not able to meet the limit even with continuous operation of a fan sized to twice the current code minimum.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Numerical Investigation and Optimization of a Flushwall Injector for Scramjet Applications at Hypervelocity Flow Conditions

An investigation utilizing Reynolds-averaged simulations (RAS) was performed in order to demonstrate the use of design and analysis of computer experiments (DACE) methods in Sandia’s DAKOTA software package for surrogate modeling and optimization. These methods were applied to a flow- path fueled with an interdigitated flushwall injector suitable for scramjet applications at hyper- velocity conditions and ascending along a constant dynamic pressure flight trajectory. The flight Mach number, duct height, spanwise width, and injection angle were the design variables selected to maximize two objective functions: the thrust potential and combustion efficiency. Because the RAS of this case are computationally expensive, surrogate models are used for optimization. To build a surrogate model a RAS database is created. The sequence of the design variables comprising the database were generated using a Latin hypercube sampling (LHS) method. A methodology was also developed to automatically build geometries and generate structured grids for each design point. The ensuing RAS analysis generated the simulation database from which the two objective functions were computed using a one-dimensionalization (1D) of the three-dimensional simulation data. The data were fitted using four surrogate models: an artificial neural network (ANN), a cubic polynomial, a quadratic polynomial, and a Kriging model. Variance-based decomposition showed that both objective functions were primarily driven by changes in the duct height. Multiobjective design optimization was performed for all four surrogate models via a genetic algorithm method. Optimal solutions were obtained at the upper and lower bounds of the flight Mach number range. The Kriging model predicted an optimal solution set that exhibited high values for both objective functions. Additionally, three challenge points were selected to assess the designs on the Pareto fronts. Further sampling among the designs of the Pareto fronts may be required to lower the surrogate model errors and perform more accurate surrogate-model-based optimization.

Shenoy, Rajiv R.↗

Parametric and sensitivity analysis of a PCM-integrated wall for optimal thermal load modulation in lightweight buildings

Load modulation in buildings is becoming increasingly important due to growing disparity in energy demand during peak and off-peak hours. Integrating phase change material (PCM) in building envelopes and using a controlled precooling strategy can provide substantial thermal load modulation; however, it may greatly increase the total energy use. Previous studies have employed PCM in building envelopes primarily for energy savings and, to some extent, peak load shedding and shifting. However, the load modulation capacity of a PCM-integrated envelope has not been well explored in the literature. In this study, we perform an extensive parametric and sensitivity analysis on PCM-integrated lightweight building walls and examine the combinatory effects of various PCM parameters on thermal load modulation and wall-related heat gains in buildings. Using numerical simulations, we investigate eight PCM parameters: PCM location in the wall, transition temperature, thickness, latent heat, transition range, density, specific heat, and thermal conductivity. Here, we evaluate their impact and relative importance to achieve maximum load modulation in buildings without compromising occupants’ thermal comfort or total energy use. The results show that the optimized PCM proposed in this study can completely invert the transient heat gain profile of the wall, providing up to 70% reduction of wall-related heat gain during peak hours without a major increase in the cumulative heat gain.

42 ENGINEERING↗

Energy performance evaluation of the ASHRAE Guideline 36 control and reinforcement learning–based control using field measurements

This study evaluates the energy performance of ASHRAE Guideline 36–compliant control (ASHRAE 36 control) and reinforcement learning (RL)–based control through experimental field tests and a simulation study. Three field tests were conducted at Oak Ridge National Laboratory’s commercial building test facility in Oak Ridge, Tennessee: a baseline with a baseline conventional control, a test with ASHRAE 36 control, and a test with RL-based control. The selected ASHRAE 36 controls were trim and respond control, as well as variable air volume (VAV) box control. We compared the measured supply air temperature of the rooftop unit, VAV box supply air temperature, and VAV box supply airflow rate across the three test cases. The field data indicated that ASHRAE 36 controls operated as specified by ASHRAE Guideline 36. Based on these data, ASHRAE 36 control achieved a 45 % reduction in hourly averaged HVAC energy consumption compared with the baseline, and RL-based control achieved a 66 % reduction. These potential annual energy savings were confirmed using a calibrated whole-building energy model. Compared with the baseline, ASHRAE 36 control reduced HVAC energy consumption by 42 %, and RL-based control achieved a 54 % reduction. Furthermore, RL-based control reduced total HVAC energy consumption by 21 % more than ASHRAE 36 control.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA Solar Sail Propulsion Technology Development

NASA's In-Space Propulsion Technology Program has developed the first generation of solar sail propulsion systems sufficient to accomplish inner solar system science and exploration missions. These first generation solar sails, when operational, will range in size from 40 meters to well over 100 meters in diameter and have an areal density of less than 13 grams per square meter. A rigorous, multi-year technology development effort culminated in 2005 with the testing of two different 20-m solar sail systems under thermal vacuum conditions. The first system, developed by ATK Space Systems of Goleta, California, uses rigid booms to deploy and stabilize the sail. In the second approach, L'Garde, Inc. of Tustin, California uses inflatable booms that rigidize in the coldness of space to accomplish sail deployment. This effort provided a number of significant insights into the optimal design and expected performance of solar sails as well as an understanding of the methods and costs of building and using them. In a separate effort, solar sail orbital analysis tools for mission design were developed and tested. Laboratory simulations of the effects of long-term space radiation exposure were also conducted on two candidate solar sail materials. Detailed radiation and charging environments were defined for mission trajectories outside the protection of the earth's magnetosphere, in the solar wind environment. These were used in other analytical tools to prove the adequacy of sail design features for accommodating the harsh space environment. Preceding and in conjunction with these technology efforts, NASA sponsored several mission application studies for solar sails. Potential missions include those that would be flown in the near term to study the sun and be used in space weather prediction to one that would use an evolved sail capability to support humanity's first mission into nearby interstellar space. This paper will describe the status of solar sail propulsion within NASA, nearterm solar sail mission applications, and near-term plans for further development.

Johnson, Les↗

Status of Solar Sail Propulsion: Moving Toward an Interstellar Probe

NASA's In-Space Propulsion Technology Program has developed the first-generation of solar sail propulsion systems sufficient to accomplish inner solar system science and exploration missions. These first-generation solar sails, when operational, will range in size from 40 meters to well over 100 meters in diameter and have an areal density of less than 13 grams-per-square meter. A rigorous, multiyear technology development effort culminated last year in the testing of two different 20-meter solar sail systems under thermal vacuum conditions. This effort provided a number of significant insights into the optimal design and expected performance of solar sails as well as an understanding of the methods and costs of building and using them. In a separate effort, solar sail orbital analysis tools for mission design were developed and tested. Laboratory simulations of the effects of long-term space radiation exposure were also conducted on two candidate solar sail materials. Detailed radiation and charging environments were defined for mission trajectories outside the protection of the earth's magnetosphere, in the solar wind environment. These were used in other analytical tools to prove the adequacy of sail design features for accommodating the harsh space environment. Preceding, and in conjunction with these technology efforts, NASA sponsored several mission application studies for solar sails, including one that would use an evolved sail capability to support humanity's first mission into nearby interstellar space. The proposed mission is called the Interstellar Probe. The Interstellar Probe might be accomplished in several ways. A 200-meter sail, with an areal density approaching 1 gram-per-square meter, could accelerate a robotic probe to the very edge of the solar system in just under 20 years from launch. A sail using the technology just demonstrated could make the same mission, but take significantly longer. Conventional chemical propulsion systems would require even longer flight times. Spinner sails of the type being explored by the Japanese may also be a good option, but the level of maturity in that technology is not clear. While the technology to support a 200-meter, ultralightweight sail mission is not yet in hand, the recent NASA investments in solar sail technology are an essential first step toward making it a reality. This paper will describe the status of solar sail propulsion within NASA, near-term solar sail mission applications, and the plan to advance the technology to the point where the Interstellar Probe mission can be flown.

Johnson, Les↗

An Operationally Based Vision Assessment Simulator for Domes

The Operational Based Vision Assessment (OBVA) simulator was designed and built by NASA and the United States Air Force (USAF) to provide the Air Force School of Aerospace Medicine (USAFSAM) with a scientific testing laboratory to study human vision and testing standards in an operationally relevant environment. This paper describes the general design objectives and implementation characteristics of the simulator visual system being created to meet these requirements. A key design objective for the OBVA research simulator is to develop a real-time computer image generator (IG) and display subsystem that can display and update at 120 frame s per second (design target), or at a minimum, 60 frames per second, with minimal transport delay using commercial off-the-shelf (COTS) technology. There are three key parts of the OBVA simulator that are described in this paper: i) the real-time computer image generator, ii) the various COTS technology used to construct the simulator, and iii) the spherical dome display and real-time distortion correction subsystem. We describe the various issues, possible COTS solutions, and remaining problem areas identified by NASA and the USAF while designing and building the simulator for future vision research. We also describe the critically important relationship of the physical display components including distortion correction for the dome consistent with an objective of minimizing latency in the system. The performance of the automatic calibration system used in the dome is also described. Various recommendations for possible future implementations shall also be discussed.

Archdeacon, John↗

PACE OCI Short-Wave Infrared Detection Assembly frequency-dependent linearity characterization and uncertainty analysis

The Ocean Color Instrument (OCI), the primary payload of the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE)observatory, will collect data to monitor the health of Earth’s oceans and atmosphere. The Short-Wave Infrared(SWIR) Detection Assembly (SDA) was built and characterized by the Utah State University Space DynamicsLaboratory (SDL) and is a subsystem of OCI. The SDA measures seven bands centered at 940, 1038, 1250, 1378,1615, 2130, and 2260 nm, with standard- and high-gain varieties for the 1250 and 1615 nm bands, resulting in nine total detection configurations in the SWIR. The delivery of high-quality science data is critically dependent upon accurately characterizing the linearity of the SDA. Two metrology techniques were employed to measure the linearity and characterize the frequency-dependent linearity uncertainty of the system. The first technique used superposition linearity measurements to determine the DC linearity, and the second technique involved an oscillating small-signal response at seven frequencies to determine the frequency-dependent linearity. Discrepancies between the DC and frequency-dependent linearities constrain the uncertainty between the two. Examining the difference between these two methods for all SDA channels, we find most channels experience an uncertainty below0.2% with a worst-case measurement uncertainty of 0.31%. Averaging SDA channels with similar detectors, optical filters, and electronics to simulate the flight-like data products yields a worst-case frequency-dependence linearity uncertainty of 0.12%, demonstrating minimal frequency dependence, implying an excellent linearity knowledge.Detailed performance knowledge, including linearity performance, verifies data quality and builds confidence in the success of the PACE mission.

PACE↗

Efficient phase-factor evaluation in quantum signal processing

Quantum signal processing (QSP) is a powerful quantum algorithm to exactly implement matrix polynomials on quantum computers. Asymptotic analysis of quantum algorithms based on QSP has shown that asymptotically optimal results can in principle be obtained for a range of tasks, such as Hamiltonian simulation and the quantum linear system problem. A further benefit of QSP is that it uses a minimal number of ancilla qubits, which facilitates its implementation on near-to-intermediate term quantum architectures. However, there is so far no classically stable algorithm allowing computation of the phase factors that are needed to build QSP circuits. Existing methods require the use of variable precision arithmetic and can only be applied to polynomials of a relatively low degree. We present here an optimization-based method that can accurately compute the phase factors using standard double precision arithmetic operations. We demonstrate the performance of this approach with applications to Hamiltonian simulation, eigenvalue filtering, and quantum linear system problems. Furthermore, our numerical results show that the optimization algorithm can find phase factors to accurately approximate polynomials of a degree larger than 10000 with errors below 10 -12 .

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Mathematical Models and Numerical Methods for High-Fidelity Simulation of Ignition of Reactive Mixtures by Nanosecond Plasma Discharges in Realistic Configurations

We present a newly developed framework for the numerical simulation of ignition of reactive mixtures using single or repeated nanosecond discharge pulses. The framework builds upon the AMReX library, using the existing compressible solver PeleC and low-Mach solver PeleLMeX and allowing for adaptive mesh refinement, complex geometries, and execution on next-generation high-performance computing (HPC) systems. High-fidelity elementary models are adopted for weakly-ionised plasma discharges with significant energy deposition, consistent with nanosecond discharge pulses, and then implemented in the solver. The treatment of non-thermal electrons and charged species, thermodynamics of non-equilbrium species, plasma kinetics, limiting time scales, and boundary conditions for charged species are discussed and addressed for computational efficiency. The framework is demonstrated for three relevant applications: single and multi-pulse discharges in air, single pulse ignition of an ethylene/air mixture, and a three-dimensional plasma discharge in air with temperature stratification. The successful application of the framework demonstrates the feasibility of high-fidelity simulation of ignition of air/hydrocarbon mixtures in three-dimensions with multiple discharge pulses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Assessing thermal resilience of an assisted living facility during heat waves and cold snaps with power outages

Extreme hot and cold weather events are becoming more frequent, intense, and longer due to climate change. When these events occur coincidentally with power outages, the resulting extreme indoor temperatures pose a severe health hazard for occupants. This study conducted a holistic modeling and analysis of an assisted living facility, where senior residents live, to assess its thermal resilience performance under a six-day heat wave in 2015 and a three-day cold snap in 2021 with power outages. Impacts of 13 energy efficiency measures on thermal resilience and backup power capacity of the facility were evaluated. Three thermal resilience metrics: the SET (standard effective temperature) degree-hours, the Heat Index, and the Hours of Safety, were used and calculated from the EnergyPlus simulation models. Furthermore, major findings are: (1) the facility would suffer from extreme temperatures during the cold and hot events without a power supply, not meeting the passive survivability requirements; (2) most passive envelope measures improve thermal resilience for both hot and cold events, but making the building envelope airtight results in conflicting performance between the hot and cold events; (3) natural ventilation is an effective measure to mitigate summer indoor overheating; and (4) the energy efficiency package can reduce backup power capacity by 19% for the three-day cold snap. It is recommended that building technologies and design strategies be evaluated to consider co-benefits of energy use, thermal resilience, and backup power needs through building energy codes or policies for existing and new buildings, which are transitioning for decarbonization and climate resilience.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A new biogeochemical modelling framework (FLaMe-v1.0) for lake methane emissions on the regional scale: development and application to the European domain

This study presents a new physical-biogeochemical modelling framework for simulating lake methane (CH 4 ) emissions at regional scales. The new model, FLaMe-v1.0 (Fluxes of Lake Methane), rests on an innovative, computationally efficient lake clustering approach that enables the simulation of CH 4 emissions across a large number of lakes. Building on the Canadian Small Lake Model (CSLM) that simulates the lake physics, we develop a suite of biogeochemical modules to simulate transient dynamics of organic Carbon (C), Oxygen (O 2 ), and CH 4 . We first test the performance of FLaMe-v1.0 by analyzing physical and biogeochemical processes in two theoretical lakes with characteristics that can be considered representative for many lakes (an oligotrophic, deep lake driven by cold climate versus a eutrophic, shallow lake driven by warm climate). Next, we evaluate the model by comparing simulated and observed timeseries of CH 4 emissions in four well-surveyed lakes. We then apply FLaMe-v1.0 at the European scale to evaluate simulated diffusive and ebullitive lake CH 4 fluxes against in-situ measurements in both boreal and central European regions. Finally, we provide a first assessment of the spatio-temporal variability in CH 4 emissions from European lakes with a surface area comprised between 0.1–1000 km 2 (n= 108 407, total area = 1.33 × 105 km 2 ), indicating a total emission of 0.97 ± 0.23 Tg CH 4 yr −1 , with the uncertainty constrained by combining FLaMe-v1.0 and machine learning techniques. Moreover, 30 % and 70 % of these CH 4 emissions are through diffusive and ebullitive pathways, respectively. Annually averaged CH 4 emission rates per unit lake area during 2010–2016 have a South-to-North decreasing gradient, resulting in a mean over the European domain as 7.39 g CH 4 m −2 yr −1 . Our simulations reveal a strong seasonality (with ice-blocking effects accounted for) in European lake CH 4 emissions, with nearly ten times higher emissions during late summer than during winter. This pronounced seasonal variation highlights the importance of accounting for the sub-annual variability in CH 4 emissions to accurately constrain regional CH 4 budgets. In the future, FLaMe-v1.0 could be embedded into Earth System Models to investigate the feedback between climate warming and global lake CH 4 emissions.

Maisonnier, Manon [Free Univ. of Brussels (Belgium↗

Software For Development Of Expert Systems

Modular software system helps create efficient artificial-intelligence computer programs. STAR*TOOL system: Set of high-level software tools; assists programmers in creation of efficient knowledge-based software systems. Provides language and capabilities for compilation of application programs written in Common LISP. Features modularity enabling elimination of unnecessary capabilities from final application program and achieves greater computing performance. Runs on any computer that supports Common LISP and has sufficient memory. Provides programmer with necessary software tools to build wide variety of reasoning and inference engines for such applications as planning, diagnosis and analysis, and simulation.

James, Mark L.↗

Coupled Stochastic Time-Inverted Lagrangian Transport/Weather Forecast and Research/Vegetation Photosynthesis and Respiration Model: Simulations of Tower-Based and Airborne CO2 Measurements - Part II

This paper evaluates simulations of atmospheric CO2 measured in 2004 at continental surface and airborne receptors, intended to test the capability to use data with high temporal and spatial resolution for analyses of carbon sources and sinks at regional and continental scales. The simulations were performed using the Stochastic Time-Inverted Lagrangian Transport (STILT) model driven by the Weather Forecast and Research (WRF) model, and linked to surface fluxes from the satellite-driven Vegetation Photosynthesis and Respiration Model (VPRM). The simulations provide detailed representations of hourly CO2 tower data and reproduce the shapes of airborne vertical profiles with high fidelity. WRF meteorology gives superior model performance compared with standard meteorological products, and the impact of including WRF convective mass fluxes in the STILT trajectory calculations is significant in individual cases. Important biases in the simulation are associated with the nighttime CO2 build-up and subsequent morning transition to convective conditions, and with errors in the advected lateral boundary condition. Comparison of STILT simulations driven by the WRF model against those driven by the Brazilian variant of the Regional Atmospheric Modeling System (BRAMS) shows that model-to-model differences are smaller than between an individual transport model and observations, pointing to systematic errors in the simulated transport. Future developments in the WRF model s data assimilation capabilities, basic research into the fundamental aspects of trajectory calculations, and intercomparison studies involving other transport models, are possible venues for reducing these errors. Overall, the STILT/WRF/VPRM offers a powerful tool for continental and regional scale carbon flux estimates.

Eluszkiewicz, Janusz↗

NASA’s Space Launch System: Progress Toward Launch

The Space Launch System (SLS), NASA’s cornerstone launch capability for a new generation of deep space exploration, has begun assembly at Kennedy Space Center (KSC) in preparation for launch in 2021. SLS will provide an unparalleled launch capability for human and robotic deep space exploration missions. Its proven propulsion system, upgrade path to more powerful vehicles, and high-volume payload fairings make it the foundation for ambitious and demanding as part of the Artemis program. Artemis is NASA’s 21st-century plan to put boots on the Moon and to perform sustainable, long-term science in deep space, with eyes toward sending explorers to Mars. The initial SLS vehicle to fly, Block 1 in the crew configuration – with the new Orion spacecraft – is scheduled to lift off from revitalized launch facilities at KSC in 2021 for an uncrewed test flight known as Artemis I. Manufacturing is complete on the vehicle and all elements have been delivered to the Exploration Ground Systems (EGS) Program, except the core stage. The program’s all-new development, the core stage is currently in the midst of a “Green Run” test campaign at Stennis Space Center (SSC). Eight progressively more challenging tests in the Green Run series will culminate in a hot-fire of four flight-proven liquid hydrogen/liquid oxygen (LH2/LOX) RS25 engines. Following the Green Run hotfiring, the core stage will ship to KSC. Already at KSC, aft sections of the fivesegment solid rocket boosters are being assembled. Previously delivered elements, including the upper stage, are undergoing final checkouts in preparation for stacking. An exciting 2021 will include such milestones as stacking SLS and Orion in KSC’s Vehicle Assembly Building (VAB), modal testing, roll out to Launch Pad 39B, Wet Dress Rehearsal (WDR), and launch. Teams across the country are preparing for launch by finalizing procedures, defining launch constraints and flight rules, training console operators, performing simulations, and more. With the SLS Block 1 vehicle for Artemis I nearing integration and launch, the second Block 1 vehicle in the crew configuration, which will carry astronauts on an Artemis II hybrid lunar flyby mission, has several elements manufactured. In fact, the solid rocket motor segments and RS-25 engines are complete. Those program elements are processing hardware for the third flight and working toward manufacturing the second SLS variant to fly, Block 1B, which will onramp a powerful new upper stage, the Exploration Upper Stage (EUS).

John Honeycutt↗

Transfer-Learnt Energy Models for Predicting Electricity Consumption in Buildings with Limited and Sparse Field Data

Modeling energy consumption is critical for energy-efficient utilization of the electric appliances in a building, smart grid programs (like demand-response), and many other smart home applications. State-of-the-art energy modeling techniques either rely on theoretical models, or extensive instrumentation of the building envelope to gather ``big" data to train a deep neural network. While theoretical models are often limited by their estimation accuracy, it is not always feasible to gather a significant amount of field data. In this paper, we explore transfer learning-based strategies to train much more accurate model for energy estimation when using a sparse field data. We transferred knowledge, in the form of data and parameters, from the simulation framework to the field data. We evaluated the efficacy of our approach on field data collected from six commercial buildings and our results indicate that transfer learning-based models trained over one month data can perform comparative (and in some cases better) than the state-of-the-art machine learning and deep learning solutions.

Jain, Milan↗

Dynamic Binary Complexes (DBC) as Super-Adjustable Viscosity Modifiers for Hydraulic Fracturing Fluids

In the preceding project year two, we refined three DBC formulations from a selection of over 50 different chemistries. The optimization study primarily encompassed testing for (i) reversibility extent, (ii) performance in the presence of chemical additives, (iii) adhesion and friction behavior during displacement in wellbores and pipelines, (iv) corrosion protection performance, and (v) injection performance with model fracture systems at the laboratory scale. Highly promising results obtained from all these tests signify the significant potential of DBCs in enhancing hydrocarbon recovery from unconventional reservoirs. The primary activities in the third project year included publishing experimental findings across multiple articles and conducting outreach initiatives. Throughout the year, we undertook tasks such as replicating experimental results, further optimizing various formulations and their associated experimental sets, and conducting additional tests to address missing components based on reviewer feedback and suggestions. We also explored the surfactant and friction-reduction aspects of selected formulations through drag reduction tests. In addition, we constructed an improved fracturing performance setup and performed flow injection tests. The specific DBC formulations focused on during this project period were A8/B1, A12/B5, and A10/B12. We also obtained results for additional DBC formulations and a select few commercial fracturing fluids for the purpose of comparison. Within the project's scope, we aim to enhance the experimental findings with the development of various models. The first two years focused on two key aspects: (i) the creation of a high-fidelity hydraulic fracturing model for non-Newtonian fluids to gain insights into the implementation of DBC fluids in fracking environments, and (ii) the development of a multiphase flow simulator for estimating total production, fluid saturation in the reservoir, and the creation of a fracture propagation model and kinetic Monte Carlo (kMC) models for diverse applications. In the third year, we delved into the fundamental nanostructural properties of DBCs, exploring aspects such as material chemistry, pH tunability, and control of DBC formation and stability. Subsequently, in the extension year, we conducted a systematic investigation of various building blocks containing primary, secondary, and tertiary amine functional groups to understand their impact on rheological and viscoelastic properties. Furthermore, we explored a Dissipative Particle Dynamics (DPD) model to simulate self-assembly processes with precision, creating a high-fidelity representation of relevant nanostructures. The tasks performed this year with the significant results obtained have been discussed in Section 2.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗