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The EGS Collab project: Outcomes and lessons learned from hydraulic fracture stimulations in crystalline rock at 1.25 and 1.5 km depth
With the goal of better understanding stimulation in crystalline rock for improving enhanced geothermal systems (EGS), the EGS Collab Project performed a series of stimulations and flow tests at 1.25 and 1.5 km depths. The tests were performed in two well-instrumented testbeds in the Sanford Underground Research Facility in Lead, South Dakota, United States. The testbed for Experiment 1 at 1.5 km depth contained two open wells for injection and production and six instrumented monitoring wells surrounding the targeted stimulation zone. Four multi-step stimulation tests targeting hydraulic fracturing and nearly year-long ambient temperature and chilled water flow tests were performed in Experiment 1. The testbed for Experiments 2 and 3 was at 1.25 km depth and contained five open wells in an outwardly fanning five-spot pattern and two fans of well-instrumented monitoring wells surrounding the targeted stimulation zone. Experiment 2 targeted shear stimulation, and Experiment 3 targeted low-flow, high-flow, and oscillating pressure stimulation strategies. Hydraulic fracturing was successful in Experiments 1 and 3 in generating a connected system wherein injected water could be collected. However, the resulting flow was distributed dynamically, and not entirely collected at the anticipated production well. Thermal breakthrough was not observed in the production well, but that could have been masked by the Joule-Thomson effect. Shear stimulation in Experiment 2 did not occur - despite attempting to pressurize the fractures most likely to shear - because of the inability to inject water into a mostly-healed fracture, and the low shear-to-normal stress ratio. The EGS Collab experiments are described to provide a background for lessons learned on topics including induced seismicity, the correlation between seismicity and permeability, distributed and dynamic flow systems, thermoelastic and pressure effects, shear stimulation, local geology, thermal breakthrough, monitoring stimulation, grouting boreholes, modeling, and system management.
Chaotic neural dynamics facilitate probabilistic computations through sampling
Cortical neurons exhibit highly variable responses over trials and time. Theoretical works posit that this variability arises potentially from chaotic network dynamics of recurrently connected neurons. Here, we demonstrate that chaotic neural dynamics, formed through synaptic learning, allow networks to perform sensory cue integration in a sampling-based implementation. We show that the emergent chaotic dynamics provide neural substrates for generating samples not only of a static variable but also of a dynamical trajectory, where generic recurrent networks acquire these abilities with a biologically plausible learning rule through trial and error. Furthermore, the networks generalize their experience in the stimulus-evoked samples to the inference without partial or all sensory information, which suggests a computational role of spontaneous activity as a representation of the priors as well as a tractable biological computation for marginal distributions. These findings suggest that chaotic neural dynamics may serve for the brain function as a Bayesian generative model.
New Insights into Dynamics and Morphology of P3HT:PCBM Active Layers in Bulk Heterojunctions
Organic photovoltaics (OPVs) are topic of extensive research for their potential application in solar cells. Recent work has led to the development of a coarse-grained model for studying poly(3-hexylthiophene) (P3HT) and [6,6]-phenyl-C 61 -butyric acid methyl ester (PCBM) blends with molecular simulations. Here we provide further validation of the force field and use it to study the thermal annealing process of P3HT:PCBM blends. A key finding of our study is that, in contrast to a previous report, the annealing process does not converge at the short time scales reported. Rather, we find that the self assembly of the blends is characterized by three rate dependent stages that require much longer simulations to approach convergence. Using state-of-the- art high performance computing, we are able to study annealing at length and time scales commensurate with devices used in experiments. Our simulations show different phase segregated morphologies dependent on the P3HT chain length and PCBM volume fraction in the blend. For short chain lengths, we observed a smectic morphology containing alternate P3HT and PCBM domains. In contrast, a phase segregated morphology containing domains of P3HT and PCBM distributed randomly in space is found for longer chain lengths. Theoretical arguments justifying stabilization of these morphologies due to shape anisotropy of P3HT (rod-like) and PCBM (sphere-like) are presented. Furthermore, results on structure factor, miscibility of P3HT and PCBM, domain spacing and kinetics of phase segregation in the blends are presented in detail. Qualitative comparison of these results with small-angle neutron scattering experiments from literature is presented and an excellent agreement is found.
Quantum quench dynamics of geometrically frustrated Ising models
Not provided.
Spatio-temporal evolution of the H → L back transition
Since ITER will operate close to threshold and with limited control, the H → L back transition is a topic important for machine operations as well as physics. Using a reduced mesoscale model [Miki et al., Phys. Plasmas 19, 092306 (2012)], we investigate ELM-free H → L back transition dynamics in order to isolate transport physics effects. Model studies indicate that turbulence spreading is the key process which triggers the back transition. The transition involves a feedback loop linking turbulence and profiles. The I-phase appears during the back transition following a slow power ramp down, while fast ramp-downs reveal a single burst of zonal flow during the back transition. The I-phase nucleates at the pedestal shoulder, as this is the site of the residual turbulence in H-mode. Hysteresis in the profile gradient scale length is characterized by the Nusselt number, where Nu=χ{sub i,turb}/χ{sub i,neo}. Relative hysteresis of temperature gradient vs density gradient is sensitive to the pedestal Prandtl number, where Pr{sub ped}=D{sub ped}/χ{sub i,neo}. We expect the H-mode to be somewhat more resilient in density than in temperature.
Comparative study and test on a two-body wave energy point absorber under various constraints.
Power generation and motion response of the floating wave energy converters is of great importance in the research topic of ocean energy harvesting. As a classic design for harvesting the ocean wave energy, the wave energy point absorber is commonly studied theoretically using the idealized 1DOF and 2DOF dynamic model based on the number of the free body within the system. Whereas the mooring system is usually ignored and only the heave motion is considered. In this paper, a point absorber is designed prototyped and tested in a water tank under three different constrains, the single body 1DOF, the two body 2DOF and the two body 6DOF. All the designs and configurations are presented in detail. Numerical analysis is conducted and presented as well to help understand the test results deeper. The test results indicate that the two body system can be tuned to match with the wave excitation and achieve higher energy absorption. In addition, the compared results between the 2DOF configuration and 6DOF configuration show that the classic 2DOF dynamic model is able to predict the performance of the point absorber with mooring well.
Variational multiscale reinforcement learning for discovering reduced order closure models of nonlinear spatiotemporal transport systems
Abstract A central challenge in the computational modeling and simulation of a multitude of science applications is to achieve robust and accurate closures for their coarse-grained representations due to underlying highly nonlinear multiscale interactions. These closure models are common in many nonlinear spatiotemporal systems to account for losses due to reduced order representations, including many transport phenomena in fluids. Previous data-driven closure modeling efforts have mostly focused on supervised learning approaches using high fidelity simulation data. On the other hand, reinforcement learning (RL) is a powerful yet relatively uncharted method in spatiotemporally extended systems. In this study, we put forth a modular dynamic closure modeling and discovery framework to stabilize the Galerkin projection based reduced order models that may arise in many nonlinear spatiotemporal dynamical systems with quadratic nonlinearity. However, a key element in creating a robust RL agent is to introduce a feasible reward function, which can be constituted of any difference metrics between the RL model and high fidelity simulation data. First, we introduce a multi-modal RL to discover mode-dependant closure policies that utilize the high fidelity data in rewarding our RL agent. We then formulate a variational multiscale RL (VMRL) approach to discover closure models without requiring access to the high fidelity data in designing the reward function. Specifically, our chief innovation is to leverage variational multiscale formalism to quantify the difference between modal interactions in Galerkin systems. Our results in simulating the viscous Burgers equation indicate that the proposed VMRL method leads to robust and accurate closure parameterizations, and it may potentially be used to discover scale-aware closure models for complex dynamical systems.
Feature Extraction for Structural Dynamics Model Validation
As structural dynamics becomes increasingly non-modal, stochastic and nonlinear, finite element model-updating technology must adopt the broader notions of model validation and uncertainty quantification. For example, particular re-sampling procedures must be implemented to propagate uncertainty through a forward calculation, and non-modal features must be defined to analyze nonlinear data sets. The latter topic is the focus of this report, but first, some more general comments regarding the concept of model validation will be discussed.
Kinetic modeling of particle dynamics in H{sup −} negative ion sources (invited)
Progress in the kinetic modeling of particle dynamics in H{sup −} negative ion source plasmas and their comparisons with experiments are reviewed, and discussed with some new results. Main focus is placed on the following two topics, which are important for the research and development of large negative ion sources and high power H{sup −} ion beams: (i) Effects of non-equilibrium features of EEDF (electron energy distribution function) on H{sup −} production, and (ii) extraction physics of H{sup −} ions and beam optics.
TF07 Snowmass Report: Theory of Collider Phenomena
Theoretical research has long played an essential role in interpreting data from high-energy particle colliders and motivating new accelerators to advance the energy and precision frontiers. Collider phenomenology is an essential interface between theoretical models and experimental observations, since theoretical studies inspire experimental analyses while experimental results sharpen theoretical ideas. This report -- from the Snowmass 2021 Theory Frontier topical group for Collider Phenomenology (TF07) -- showcases the dynamism, engagement, and motivations of collider phenomenologists by exposing selected exciting new directions and establishing key connections between cutting-edge theoretical advances and current and future experimental opportunities. By investing in collider phenomenology, the high-energy physics community can help ensure that theoretical advances are translated into concrete tools that enable and enhance current and future experiments, and in turn, experimental results feed into a more complete theoretical understanding and motivate new questions and explorations.
TF07 Snowmass Report: Theory of Collider Phenomena
Theoretical research has long played an essential role in interpreting data from high-energy particle colliders and motivating new accelerators to advance the energy and precision frontiers. Collider phenomenology is an essential interface between theoretical models and experimental observations, since theoretical studies inspire experimental analyses while experimental results sharpen theoretical ideas. Here, this report -- from the Snowmass 2021 Theory Frontier topical group for Collider Phenomenology (TF07) -- showcases the dynamism, engagement, and motivations of collider phenomenologists by exposing selected exciting new directions and establishing key connections between cutting-edge theoretical advances and current and future experimental opportunities. By investing in collider phenomenology, the high-energy physics community can help ensure that theoretical advances are translated into concrete tools that enable and enhance current and future experiments, and in turn, experimental results feed into a more complete theoretical understanding and motivate new questions and explorations.
Achievement of the Planetary Defense Investigations of the Double Asteroid Redirection Test (DART) Mission
NASA's Double Asteroid Redirection Test (DART) mission was the first to demonstrate asteroid deflection, and the mission's Level 1 requirements guided its planetary defense investigations. Here, we summarize DART's achievement of those requirements. On 2022 September 26, the DART spacecraft impacted Dimorphos, the secondary member of the Didymos near-Earth asteroid binary system, demonstrating an autonomously navigated kinetic impact into an asteroid with limited prior knowledge for planetary defense. Months of subsequent Earth-based observations showed that the binary orbital period was changed by –33.24 minutes, with two independent analysis methods each reporting a 1 σ uncertainty of 1.4 s. Dynamical models determined that the momentum enhancement factor, β , resulting from DART's kinetic impact test is between 2.4 and 4.9, depending on the mass of Dimorphos, which remains the largest source of uncertainty. Over five dozen telescopes across the globe and in space, along with the Light Italian CubeSat for Imaging of Asteroids, have contributed to DART's investigations. These combined investigations have addressed topics related to the ejecta, dynamics, impact event, and properties of both asteroids in the binary system. A year following DART's successful impact into Dimorphos, the mission has achieved its planetary defense requirements, although work to further understand DART's kinetic impact test and the Didymos system will continue. In particular, ESA's Hera mission is planned to perform extensive measurements in 2027 during its rendezvous with the Didymos–Dimorphos system, building on DART to advance our knowledge and continue the ongoing international collaboration for planetary defense.
Smart Grid Integration Laboratory
The initial federal funding for the Colorado State University Smart Grid Integration Laboratory is through a Congressionally Directed Project (CDP), DE-OE0000070 Smart Grid Integration Laboratory. The original program requested in three one-year increments for staff acquisition, curriculum development, and instrumentation all which will benefit the Laboratory. This report focuses on the initial phase of staff acquisition which was directed and administered by DOE NETL/ West Virginia under Project Officer Tom George. Using this CDP funding, we have developed the leadership and intellectual capacity for the SGIC. This was accomplished by investing (hiring) a core team of Smart Grid Systems engineering faculty focused on education, research, and innovation of a secure and smart grid infrastructure. The Smart Grid Integration Laboratory will be housed with the separately funded Integrid Laboratory as part of CSU's overall Smart Grid Integration Center (SGIC). The period of performance of this grant was 10/1/2009 to 9/30/2011 which included one no cost extension due to time delays in faculty hiring. The Smart Grid Integration Laboratory's focus is to build foundations to help graduate and undergraduates acquire systems engineering knowledge; conduct innovative research; and team externally with grid smart organizations. Using the results of the separately funded Smart Grid Workforce Education Workshop (May 2009) sponsored by the City of Fort Collins, Northern Colorado Clean Energy Cluster, Colorado State University Continuing Education, Spirae, and Siemens has been used to guide the hiring of faculty, program curriculum and education plan. This project develops faculty leaders with the intellectual capacity to inspire its students to become leaders that substantially contribute to the development and maintenance of Smart Grid infrastructure through topics such as: (1) Distributed energy systems modeling and control; (2) Energy and power conversion; (3) Simulation of electrical power distribution system that integrates significant quantities of renewable and distributed energy resources; (4) System dynamic modeling that considers end-user behavior, economics, security and regulatory frameworks; (5) Best practices for energy management IT control solutions for effective distributed energy integration (including security with the underlying physical power systems); (6) Experimental verification of effects of various arrangements of renewable generation, distributed generation and user load types along with conventional generation and transmission. Understanding the core technologies for enabling them to be used in an integrated fashion within a distribution network remains is a benefit to the future energy paradigm and future and present energy engineers.
Evaporation Induced Entrainment of Contaminants from Evaporating and Burning Liquids.
This interim report details model development, theory, and a literature review focusing on the evaporation induced entrainment (sub-boiling) of contaminated liquids. Entrainment from a variety of sources is the topic of DOE Handbook 3010, and this report deals more broadly with fire related airborne sources of contaminants in hazardous operations. Relatively few studies have examined sub-boiling behavior in the past, however, it can be a phenomenon that presents a fire related risk under hazardous operations. Molecular dynamics simulations are used to infer the gaseous evolution of coordinated complexes, and a model for a water/plutonium/nitrate system is deduced from the simulation results by evaluating the statistical trends of the results. Questions remain as to the chemical reactivity and longevity of entrained species. A generalized computer model capability and simple analytical model assumptions are developed for predicting the results of these and other (boiling and solid entrainment) scenarios. Verification related predictions using these models are illustrated.
Structure and Performance of GFDL's CM4.0 Climate Model
We illustrate the Geophysical Fluid Dynamics Laboratory's CM4.0 physical climate model, with emphasis on those aspects that may be of particular importance to users of this model and its simulations. The model is built with the AM4.0/LM4.0 atmosphere/land model and OM4.0 ocean model. Topics include the rationale for key choices made in the model formulation, the stability as well as drift of the preindustrial control simulation, and comparison of key aspects of the historical simulations with observations from recent decades. Notable achievements include the relatively small biases in seasonal spatial patterns of top-of-atmosphere fluxes, surface temperature, and precipitation; reduced double Intertropical Convergence Zone bias; dramatically improved representation of ocean boundary currents; a high-quality simulation of climatological Arctic sea ice extent and its recent decline; and excellent simulation of the El Niño-Southern Oscillation spectrum and structure. Areas of concern include inadequate deep convection in the Nordic Seas; an inaccurate Antarctic sea ice simulation; precipitation and wind composites still affected by the equatorial cold tongue bias; muted variability in the Atlantic Meridional Overturning Circulation; strong 100 year quasiperiodicity in Southern Ocean ventilation; and a lack of historical warming before 1990 and too rapid warming thereafter due to high climate sensitivity and strong aerosol forcing, in contrast to the observational record. Overall, CM4.0 scores very well in its fidelity against observations compared to the Coupled Model Intercomparison Project Phase 5 generation in terms of both mean state and modes of variability and should prove a valuable new addition for analysis across a broad array of applications.
Cosmological perturbation theory in 1+1 dimensions
Many recent studies have highlighted certain failures of the standard Eulerian-space cosmological perturbation theory (SPT). Its problems include (1) not capturing large-scale bulk flows [leading to an O( 1) error in the 1-loop SPT prediction for the baryon acoustic peak in the correlation function], (2) assuming that the Universe behaves as a pressureless, inviscid fluid, and (3) treating fluctuations on scales that are non-perturbative as if they were. Recent studies have highlighted the successes of perturbation theory in Lagrangian space or theories that solve equations for the effective dynamics of smoothed fields. Both approaches mitigate some or all of the aforementioned issues with SPT. We discuss these physical developments by specializing to the simplified 1D case of gravitationally interacting sheets, which allows us to substantially reduces the analytic overhead and still (as we show) maintain many of the same behaviors as in 3D. In 1D, linear-order Lagrangian perturbation theory ('the Zeldovich approximation') is exact up to shell crossing, and we prove that n{sup th}-order Eulerian perturbation theory converges to the Zeldovich approximation as narrow ∞. In no 1D cosmology that we consider (including a CDM-like case and power-law models) do these theories describe accurately the matter power spectrum on any mildly nonlinear scale. We find that theories based on effective equations are much more successful at describing the dynamics. Finally, we discuss many topics that have recently appeared in the perturbation theory literature such as beat coupling, the shift and smearing of the baryon acoustic oscillation feature, and the advantages of Fourier versus configuration space. Our simplified 1D case serves as an intuitive review of these perturbation theory results.