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At least 973 records · Page 54

Numerical investigation of multiphase flow through self-affine rough fractures

Multiphase flow through fractures has great significance in subsurface energy recovery and gas storage applications. Different fracture and flow properties affect flow through a fracture which is difficult to control in laboratory experiments. Here, we perform lattice Boltzmann simulations in an ensemble of synthetically generated fractures. Drainage simulations are performed at different capillary numbers, wettability, and viscosity ratios. We track the invading front and quantify breakthrough saturations and show that roughness and wettability have a strong effect on fluid invasion through a complex fracture. Invading a more viscous fluid results in more stable displacement regardless of the capillary number while at very low capillary numbers, fluid migration is dependent on the inherent structure of the fracture. We develop a fluid displacement phase diagram in a single rough fracture and compare our results from that in the literature. Finally, we extend the phase diagrams across multiple fractures and demonstrate the importance of natural fracture features of roughness and wettability in identifying stable versus unstable displacement regimes during multiphase flow through rough fractures. Our work presents an end-to-end numerical pathway for testing on experimental data and expanding numerical data sets for testing combinations of different physical phenomenon and make valuable predictions on fluid flow through rough fractures.

02 PETROLEUM↗

Optimized Illuminance Operation-A Light-Driven Dilution Strategy to Improve Microalgae Biomass Productivity

Periodic dilution is a necessary operation to avoid light limitation due to self-shading as the culture grows dense. However, environmental conditions are constantly changing in outdoor cultivation systems, making it difficult to determine the optimal dilution rate. To address this challenge, this study evaluated a dilution approach based on light penetration to optimize illuminance (OptiLum) in the culture. Biomass concentration was controlled via sensor-feedback directed dilution to ensure that light reaching the bottom of the culture was maintained above the compensation intensity. Under replicated outdoor pond conditions, by keeping the entire culture within a net-positive photosynthetic zone, the OptiLum operation improved the biomass productivities of two top-performing strains, Picochlorum celeri and Tetraselmis striata, by 95 % and 86 %, respectively, compared to conventional semi-continuous batch cultivation. The dilution rate varied daily and was dynamically adjusted based on the light status within the culture, which is concurrently influenced by weather, culture density, and growth rate. The techno-economic analysis showed that the OptiLum operation could reduce biomass production cost by as much as 24 % and 33 % for P. celeri and T. striata, respectively, assuming a low-cost dewatering approach with initial gravity settling of biomass can be realized for both strains. However, a more costly two-stage dewatering strategy, comprising only membranes and centrifuges, may be necessary for non-settling strains, such as P. celeri, which would alternatively increase production costs by 23 % for the OptiLum case. The results demonstrated that the proposed OptiLum operation is a promising approach to improve biomass productivity and lower production cost via weather-responsive and self-adjusting dilution.

09 BIOMASS FUELS↗

Hazard analysis for identifying common cause failures of digital safety systems using a redundancy-guided systems-theoretic approach

Replacing the existing aging analog instrumentation and control (I&C) systems with modern safety control and protection, digital technology offers one of the foremost means of performance improvements and cost reductions for the existing nuclear power plants (NPPs). However, the qualification of digital I&C systems remains a challenge, especially considering the issue of software common-cause failures (CCFs), which are difficult to address. With the application and upgrades of advanced digital I&C systems, software CCFs have become a potential threat to plant safety because most redundant designs use similar digital platforms or software in the operating and application systems. With complex designs of multilayer redundancy to meet the single-failure criterion, digital I&C safety systems (e.g., engineered safety-features actuation system [ESFAS]) are of a particular concern in the U.S. Nuclear Regulatory Commission (NRC) licensing procedures. Here, this paper applies a modularized approach to conduct redundancy-guided systems-theoretic hazard analysis for an advanced digital ESFAS with multilevel redundancy designs. Systematic methods and risk-informed tools are incorporated to address both hardware and software CCFs, which provide guidance to eliminate the causal factors of potential single points of failure in the design of digital safety systems in advanced plant designs.

42 ENGINEERING↗

Pre-trained network-based transfer learning: A small-sample machine learning approach to nuclear power plant classification problem

Some research topics belonging to classification problems in the nuclear industry, such as fault diagnosis and accident identification, can be solved by feature extraction and subsequent application of statistical machine learning classifiers. Recently, deep neural network-based methods with automatic feature extraction and high accuracy have gained wide attention. They usually require large-scale training data, however, plant fault or accident data are scarce or difficult to obtain. Here this paper proposes a convolutional network (CNN)-based transfer learning method to solve this problem. The network's shallow layer is derived from a pre-trained CNN based on the ImageNet database to automatically extract features, and the deep layer is customized to match the classification problem. Data in non-image formats are converted to image formats and subsequently used to train the network. Case studies of rotating machines fault diagnosis show that the proposed method requires only limited training data to achieve high accuracy.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A Hybrid Domain Overlapping Method for Coupling System Thermal Hydraulics and CFD Codes

A hybrid multiscale coupling methodology based on a domain overlapping approach has been developed for coupling System Thermal Hydraulics (STH) and Computational Fluid Dynamics (CFD) codes. The method has been implemented between the modern STH code SAM and the CFD code NekRS, using the coupling tool Cardinal. The coupling aims to extend the STH code's applicability to scenarios where local momentum and energy transfers are important yet difficult for STH codes to capture, such as three-dimensional mixing. Two coupling strategies are implemented and compared: a hybrid domain overlapping method and the conventional domain decomposition method. Here, the strategies are applied to two closed-loop applications, and the present method shows superior stability behavior when compared to the domain decomposition method. Then, the present coupling method is validated against experimental data from a double T-junction experiment. The present STH/CFD coupling shows improved agreement with experimental data when compared to STH standalone simulations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Preliminary verification of the MCNP perturbation and fixed-source tally sensitivity tools

Integral benchmark experiments are vital in the adjustment and validation of the nuclear data that govern predictive simulations across the nuclear community. The nuclear data sensitivity capabilities of the Monte Carlo N-Particle (MCNP ®) transport code are currently limited; however, expanding sensitivity capabilities will allow benchmark experiments to be designed to resolve compensating errors and adjust nuclear data where previously prohibitively difficult. This paper provides details of a preliminary verification for the use of (i.) the recently revised perturbation and (ii.) developmental fixed-source sensitivity tools within MCNP to calculate sensitivities of tallied responses (such as current integrated over a surface, F1, and flux averaged over a cell, F4) to nuclear data in fixed-source simulations. Energy-binned and energy-integrated sensitivities calculated with these tools are compared against sensitivities calculated using a central-difference approximation. Here, the verification is completed for four configurations of a benchmarked system using a 4.5-kg plutonium sphere surrounded by varying amounts of copper and/or polyethylene. The results show that sensitivities calculated with the perturbation and fixed-source sensitivity tools agree with the central-difference-based approach.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Preliminary studies on diversion and misuse for TRISO-fueled heat-pipe-cooled microreactors

Microreactors are being developed by multiple reactor designers to mass-produce nuclear facilities for worldwide deployment. Including microreactors in a country’s energy portfolio introduces new concerns for international safeguards regarding the number of reactor locations. Microreactors have smaller quantities of nuclear material compared to current light-water reactors, which makes diverting enough material for clandestine purposes difficult for a single reactor. Diversion or misuse of multiple microreactors to obtain a significant quantity introduces a new acquisition pathway. This work examines diversion and misuse scenarios for a realistic heat-pipe-cooled microreactor to understand how these scenarios would effect reactor operations to determine if monitoring key parameters could reduce the burden of inspection on monitoring agencies. Here, we determined misuse caused too drastic of an effect on core operations to be a valid acquisition pathway for the realistic heat-pipe-cooled microreactor. Diversion was explored across varying levels of severity, where potential diversion scenarios could yield one significant quantity of material from between six and eleven microreactors. Through examining the critical control drum angle, excess reactivity, control drum worth, and power distribution changes from nominal were detected over the operational lifetime, which could indicate a divergence from normal operations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Parameter Study of the Running-In Process for the Generic Pebble Bed Reactor (GPBR200)

The run-in period of a pebble bed reactor is complex and difficult to model given significant heterogeneity in core composition, power, and temperature. While it is understood that the initial composition of the core should eventually result in the same equilibrium core composition, the approach to equilibrium can vary significantly depending on factors such as start-up fuel enrichment and power ramp rate. To explore this, a high-fidelity model of the General Pebble Bed Reactor was used to vary power ramp schemes and start-up core compositions. It was found that both the initial core composition and power ramp rate had a significant impact on the flow rate of pebbles during early time steps, with higher ramp rates and low enrichment resulting in non-physical flow rates. Power ramp rate alone was found to dictated maximum pebble power peaking observed during the run-in process, with higher ramp rates resulting in greater peak pebble powers. Start-up fuel enrichment and power ramp were found to both impact total fuel consumption, although the impact of start-up fuel enrichment was generally secondary to ramp rate.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DC conductivity from backreacted non-linear arcsin electrodynamics

Highlights: • This model, reproduces conductivity and Hall angle of high-T{sub c} cuprates. • It exhibits metal-insulator transition under variation of magnetic field. • Obtained transport properties for a backreacted non-linear electrodynamics model. - Abstract: We consider arcsin electrodynamics in a holographic set up along with dilatonic and axionic scalar fields. Considering backreaction of the matter fields on the geometry we study direct conductivity of the dual theory and obtain the conductivity matrix. Since obtaining an exact solution is difficult in general, we have studied several limiting cases. In particular, at the strong momentum dissipation limit, we find for hyperscaling violating geometry as the background, the resistivity and Hall coefficient will behave as ∼T and ∼T{sup 2} respectively. Then we restrict to a simpler model, where we find that the variation of the magnetic field can lead to metal–insulator transition/crossover.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Local indistinguishability and incompleteness of entangled orthogonal bases: Method to generate two-element locally indistinguishable ensembles

Highlights: • Local indistinguishability of orthogonal quantum states. • Bipartite and multipartite quantum ensembles. • Unextendible entangled bases and uncompletable entangled bases. • Two-element locally indistinguishable quantum ensembles. • Multiparty unextendible entangled bases with unextendibility in all partitions. We relate the phenomenon of local indistinguishability of orthogonal states with the properties of unextendibility and uncompletability of entangled bases for bipartite and multipartite quantum systems. We prove that all two-qubit unextendible entangled bases are of size three and they cannot be perfectly distinguished by separable measurements. We identify a method of constructing two-element orthogonal ensembles, based on the concept of unextendible entangled bases, that can potentially lead to information sharing applications. Two-element ensembles form the fundamental unit of ensembles, and yet does not offer locally indistinguishable ensembles for pure state elements. Going over to mixed states does open this possibility, but can be difficult to identify. The method provided using unextendible entangled bases can be used for their systematic generation. In multipartite systems, we find a class of unextendible entangled bases for which the unextendibility property remains conserved across all bipartitions. We also identify nonlocal operations, local implementation of which require entangled resource states from a higher-dimensional quantum system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Monitoring of mechanical changes in a pipe assembly with complex geometry using multi-mode acoustic signals

Guided wave ultrasonic testing has been widely used for nondestructive and long-range evaluation of diverse mechanical structures, such as pipes and plates. In general, a large number of guided wave modes exist even in the simplest geometries, and they exhibit highly dispersive characteristics. Thus, sophisticated excitation methods and elaborate modal analyses need to be implemented to excite, acquire, and process well-defined pure modes as part of such a measurement method. If the interrogated structure has complex geometry, for example, with cross-sectional variations or multiple joints, the utilization of pure modes becomes significantly more difficult. To overcome this difficulty, this paper proposes the use of multi-mode, multi-frequency guided waves for long-range inspection of structures with arbitrarily complex geometries. Furthermore, using broadband chirp signals and multi-mode time–frequency analysis in a prototypical complex pipe assembly that includes multiple pipe diameters, elbows, and flange connections, we experimentally show sensitive detection of mechanical changes (both material addition and loss). In addition, we demonstrate that the complexity of the structure can be modeled in the digital domain with sufficient detail to allow accurate numerical simulation of the acoustic response using this method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A comparative techno-economic analysis of renewable methanol synthesis from biomass and CO 2 : Opportunities and barriers to commercialization

Global demand for methanol as both a chemical precursor and a fuel additive is rising. At the same time, numerous renewable methanol production pathways are under development, which, if commercialized, could provide significant environmental benefits over traditional methanol synthesis pathways. However, it is difficult to compare technologies at different maturity levels, with differing feedstocks, and with significant differences in overall process design. Thus, there is a need to harmonize the analyses of renewable pathways using a consistent techno-economic approach to evaluate the potential for commercialization of various pathways. This analysis uses a novel cross-comparison method to assess near-term and long-term viability of both low- and high-maturity level technologies. Furthermore, the techno-economic assessment considers cost factors critical to market acceptance combined with carbon- and energy-efficiency assessments of three renewable pathways compared with a commercial baseline. We find that biomass gasification to methanol represents a near-term viable pathway with a high technology readiness level and commercially competitive market price. If cost-reducing technological improvements can be realized and scaled up in the CO 2 electrolysis pathways, the potential for higher carbon efficiencies may help drive market adoption of these more modular, direct conversion pathways in future markets as they present an opportunity to better support global decarbonization efforts through efficient waste carbon utilization.

09 BIOMASS FUELS↗

Energy sector portfolio analysis with uncertainty

Governments are dealing with the challenge of how to efficiently invest in research and development portfolios related to energy technologies. Research and development investment decisions in the energy space are especially difficult due to numerous risks and uncertainties, and due to the complexity of energy's interactions with the broad economy. Historically, much of the U.S. Department of Energy's in-depth research and development analyses focused on assessing the impact of a research and development activity in isolation from other available opportunities and did not substantially consider risk and uncertainty. Endeavoring to combine integrated energy-economy modeling with uncertainty analysis and technology-specific research and development activities, the U.S. Department of Energy commissioned the development of the Stochastic Energy Deployment System to support and improve public energy research and development decision-making. The Stochastic Energy Deployment System draws from expert-elicited probability distributions for research and development-driven improvements in technology cost and performance, and it uses Monte Carlo simulations to evaluate the likelihood of outcomes within a system dynamics energy-economy model. The framework estimates the uncertain benefits and costs of various research and development portfolios and provides insight into the probability of meeting national technology goals, while accounting for interactions with the larger economy and for interactions among research and development investments spanning many energy sectors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Implementing multi-settlement decentralized electricity market design for transactive communities with imperfect communication

Recent advances in information and communication technologies and smart metering, provides strategic opportunities for ``prosumers" to reform their conventional energy practices towards more consumer-centric economies. From an operational perspective, managing power distribution networks is becoming more difficult with such active grid-edge systems providing limited to no visibility or control. Transactive Energy (TE) has been emerging as a key enabler towards effectively and efficiently integrating prosumers into competitive electricity markets. This work presents a transactive implementation of community-centric markets. A co-simulation framework is developed for evaluating the proposed market structure with high-fidelity models. Case studies on the IEEE-123 node test system demonstrate that community-centric transactive markets can enable communities of prosumers to operate collaboratively as grid-edge systems. The potential benefits of implementing community-centric TE systems are also illustrated.

Mukherjee, Monish↗

Model-Free Voltage Control of Active Distribution System with PVs Using Surrogate Model-Based Deep Reinforcement Learning

Accurate knowledge of the distribution system topology and parameters is required to achieve good voltage control performance, but this is difficult to obtain in practice. This paper proposes a physical-model-free voltage control method based on a surrogate-model-enabled deep reinforcement learning approach. Specifically, a surrogate model is trained in a supervised manner using the recorded limited number of historical data to learn the relationship between the power injections and voltage fluctuations of each node. Then, the deep reinforcement learning algorithm is applied to learn an optimal control strategy from the experiences obtained by continuous interactions with the surrogate model. The proposed method can achieve physical-model-free control of unbalanced distribution network and inform real-time decisions to deal with fast voltage fluctuations caused by the rapid variation of PV generation. Simulation results on an unbalance IEEE 123-bus system show that the proposed method can achieve similar performance as that of perfect physical-model-based approaches while being advantageous over other traditional methods.

active distribution network↗

Programmable intrusion detection for distributed energy resources in cyber–physical networked microgrids

We present a programmable intrusion detection method is presented to identify the malicious attacks to distributed energy resources (DERs) in the cyber-physical networked microgrids. The proposed method injects small programmable signals into the system and uses the response to identify abnormal conditions. Because of the low or even zero inertia induced by integrations of DER power-electronic-interfaces, microgrids have very limited resilience capability; and thus, being sensitive to attacks. One microgrid's malfunction caused by attacks can easily propagate to its neighboring systems when several microgrids are connected, leading to catastrophic electricity supply failures. Through the presented method, malicious intrusions can be effectively detected, located, and defended for securing microgrids. Theoretical derivations are provided to define the programmable detection rules. The detection rule is easy and flexible to update, making it difficult for attack actors to gain the knowledge of the detection rules, in order to avoid being detected. Numerical results on a cyber-physical networked microgrids system show that the proposed method is effective and efficient in precisely locating intrusion attacks to the microgrids system.

42 ENGINEERING↗

A comparison of building system parameters between affordable and market-rate housing in New York City

Low-income households in the United States experience higher than average energy burdens (defined as the proportion of household income spent on energy utilities), and many of these households struggle to simultaneously pay for rent, energy, and basic household necessities. The analysis presented here in this study examines whether the underlying characteristics of buildings and their energy systems could contribute to this disparity for affordable housing residents in New York City. It combines an energy audit dataset of 7,328 multifamily buildings with a database of properties receiving local, state, or federal housing subsidies. The results of this analysis indicate that the building-level installed equipment in large (greater than 50,000 square feet) affordable housing buildings in New York City is more efficient than that in market-rate buildings, but this trend largely disappears when considering overall building characteristics, such as location, size, or age. Significant differences in the types of systems installed in affordable and market-rate housing are also observed, as well as the types of energy efficiency recommendations made by energy auditors. However, these latter data were not normalized by building system characteristics, as that analysis is much more difficult to interpret for categorical data such as heating system type. These findings indicate that retrofit policies and building performance standards focused on affordable housing will likely need to account for underlying differences in building characteristics between affordable and market-rate housing to achieve intended impacts.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Enhancing flexibility for climate change using seasonal energy storage (aquifer thermal energy storage) in distributed energy systems

Long-term energy storage is expected to play a vital role in the deep decarbonization of building energy sectors, while enhancing the flexibility of buildings to withstand future climate variations. However, it is challenging to design distributed multi-energy systems (DMES) while taking into account the uncertainties introduced by climate change, since stochastic optimization of such systems is difficult. The present study introduces a stochastic optimization model to address this bottleneck, taking into account DMES including aquifer thermal energy storage (ATES) as the long-term thermal storage. For the first time, a novel optimization algorithm links ATES with the DMES optimization model with the support of a simplified geotechnical model. Subsequently, a case study was conducted, focusing on a residential district in Chicago where the impact of future climate condition, energy demand, and solar and wind energy potentials were evaluated using Weather Research and Forecasting (WRF) data (up to 2080) and the EnergyPlus model. The study revealed that ATES is an attractive way to improve the renewable energy penetration level and minimize the dependence on fossil fuels with reasonable support from the grid to assist the fluctuations in both demand and generation. Furthermore, ATES notably reduces fuel consumption and dependence while greatly enhancing the flexibility of the energy system to withstand fluctuations in demand and renewable energy generation brought by future climate variations. These qualities will make ATES an important part of distributed energy systems, even though it is not currently the lowest cost alternative due to lack of technology maturity. Furthermore, the design platform introduced in the present study can be used to design DMES enhancing flexibility to accommodate future climate variations.

25 ENERGY STORAGE↗