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Zhu, Hao

Publications and source records attributed to Zhu, Hao.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Distribution System Behind-the-Meter DERs: Estimation, Uncertainty Quantification, and Control

This paper summarizes the three-year technical activities of the IEEE Task Force (TF) on behind-the-meter (BTM) distributed energy resources (DERs): estimation, uncertainty quantification, and control. The potential grid services from BTM DERs are discussed in detail. The paper also reviews the state-of-the-art for BTM DERs visibility, uncertainty quantification, and, optimization and control. Furthermore, different aspects of the market structures associated with BTM DERs are covered, including emerging market and business models. Finally, needs and recommendations are provided for additional areas such as system protection, computing capabilities, algorithm development, market structure design, cyberinfrastructure and security, and hardware and software developments.

behind-the-meter↗
DOE OSTI2024

Methodology for Good Machine Learning with Multi‐Omics Data

In 2020, Novartis Pharmaceuticals Corporation and the U.S. Food and Drug Administration (FDA) started a 4‐year scientific collaboration to approach complex new data modalities and advanced analytics. The scientific question was to find novel radio‐genomics‐based prognostic and predictive factors for HR+/HER− metastatic breast cancer under a Research Collaboration Agreement. This collaboration has been providing valuable insights to help successfully implement future scientific projects, particularly using artificial intelligence and machine learning. This tutorial aims to provide tangible guidelines for a multi‐omics project that includes multidisciplinary expert teams, spanning across different institutions. We cover key ideas, such as “maintaining effective communication” and “following good data science practices,” followed by the four steps of exploratory projects, namely (1) plan, (2) design, (3) develop, and (4) disseminate. We break each step into smaller concepts with strategies for implementation and provide illustrations from our collaboration to further give the readers actionable guidance.

Pharmacology & Pharmacy↗
DOE OSTI2023

Risk-Constrained Reinforcement Learning for Inverter-Dominated Power System Controls

Here, this paper develops a risk-aware controller for grid-forming inverters (GFMs) to minimize large frequency oscillations in GFM inverter-dominated power systems. To tackle the high variability from loads/renewables, we incorporate a mean-variance risk constraint into the classical linear quadratic regulator (LQR) formulation for this problem. The risk constraint aims to bound the time-averaged cost of state variability and thus can improve the worst-case performance for large disturbances. The resulting risk-constrained LQR problem is solved through the dual reformulation to a minimax problem, by using a reinforcement learning (RL) method termed as stochastic gradient-descent with max-oracle (SGDmax). In particular, the zero-order policy gradient (ZOPG) approach is used to simplify the gradient estimation using simulated system trajectories. Numerical tests conducted on the IEEE 68-bus system have validated the convergence of our proposed SGDmax for GFM model and corroborate the effectiveness of the risk constraint in improving the worst-case performance while reducing the variability of the overall control cost.

Frequency control↗
DOE OSTI2023

Reinforcement Learning-based Output Structured Feedback for Distributed Multi-Area Power System Frequency Control

Load frequency control (LFC) is a key factor to maintain the stable frequency in multi-area power systems. As the modern power systems evolve from centralized to decentralized paradigm, LFC needs to consider the decentralized scheme that considers limited information from the information-exchange graph for the generator control of each interconnected area. This paper aims to solve a data-driven constrained LQR problem with mean-variance risk constraints and output structured feedback, and applies this framework to solve the LFC problem in multi-area power systems. By reformulating the constrained optimization problem into a minimax problem, the stochastic gradient descent max-oracle (SGDmax) algorithm with zero-order policy gradient (ZOPG) is adopted to find the optimal feedback gain from the learning, while guaranteeing the convergence. In addition, to improve the adaptation of the proposed learning method to new or varying models, we construct an emulator grid that approximates the dynamics of a physical grid and performs training based on this model. Once the feedback gain is obtained from the emulator grid, it is applied to the physical grid with a robustness test to check whether the controller from the approximated emulator applies to the actual system. Numerical tests show that the obtained feedback controller can successfully control the frequency of each area, while mitigating the uncertainty from the loads, with reliable robustness that ensures the adaptability of the obtained feedback gain to the actual physical grid.

Kwon, Kyung-bin↗
DOE OSTI2023

Ultrafast CMOS image sensors and data-enabled super-resolution for multimodal radiographic imaging and tomography

We summarize recent progress in ultrafast Complementary Metal Oxide Semiconductor (CMOS) image sensor development and the application of neural networks for post-processing of CMOS and charge-coupled device (CCD) image data to achieve sub-pixel resolution (thus ‘super-resolution’). The combination of novel CMOS pixel designs and data-enabled image post-processing provides a promising path towards ultrafast high-resolution multi-modal radiographic imaging and tomography applications.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

The Association Between Baseline Hepatic or Renal Function and Clinical Outcomes for Patients With Non–Small Cell Lung Cancer Treated With a PD –1/PD– L1 Blocking Antibody Using Real–World and Trial Data

Clinical trials have demonstrated the benefit of PD-1/PD-L1 blocking antibodies for the treatment of patients with advanced non-small cell lung cancer (NSCLC) in defined patient populations that often exclude patients with moderate or severe hepatic or renal impairment. We assessed the association between overall survival (OS) and baseline organ function in patients with advanced NSCLC treated with PD-1/PD-L1 blocking antibodies in real-world data (RWD; patient-level data from electronic health records) and pooled clinical trial data submitted to the US Food and Drug Administration (FDA). The Kaplan–Meier estimator was used to estimate OS in different subgroups based on organ function. Unadjusted and adjusted Cox proportional hazards models were used to estimate the association between OS and organ function. In this hypothesis-generating study, baseline renal impairment did not appear to be associated with OS, while patients with baseline liver impairment had shorter OS. RWD provided information on a broader range of renal and hepatic function than was evaluated in clinical trials and hold promise to complement trial data in better understanding populations not represented in clinical trials.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Ultrafast CMOS image sensors and data-enabled super-resolution for multimodal radiographic imaging and tomography

We summarize recent progress in ultrafast Complementary Metal Oxide Semiconductor (CMOS) image sensor development and the application of neural networks for post-processing of CMOS and charge-coupled device (CCD) image data to achieve sub-pixel resolution (thus $super$-$resolution$). The combination of novel CMOS pixel designs and data-enabled image post-processing provides a promising path towards ultrafast high-resolution multi-modal radiographic imaging and tomography applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Substation-Level Grid Topology Optimization Using Bus Splitting

Operations of substation circuit breakers are important for maintenance needs and topology reconfiguration in power systems. Bus splitting is one type of topology change where the two bus bars at a substation can become electrically disconnected under certain actions of circuit breakers. Because these events involve detailed substation modeling, they are typically not considered in routine power system operation and control. In this paper, an improved substation-level topology optimization framework is developed by expanding traditional line switching decisions by breaker-level bus splitting, which can further reduce grid congestion and generation costs. A tight McCormick relaxation is proposed to reformulate the bilinear terms in the resultant optimization problem to linear inequality constraints. Thus, a tractable mixed-integer linear program reformulation is attained that allows for efficient solutions in real-time operations. Numerical studies on the IEEE 14-bus and 118-bus systems demonstrate the computational performance and economic benefits of the proposed topology optimization approach.

bus split↗
DOE OSTI2021

Substation-Level Grid Topology Optimization Using Bus Splitting: Preprint

Operations of substation circuit breakers are of high significance for performing system maintenance and topology optimization. Bus splitting is one type of topology changes where the two bus-bars at a substation become electrically disconnected after certain actions of circuit breakers. As these events involve detailed substation modeling, they are not typically considered in power system routine operation and control. In this paper, an improved substation-level topology optimization is developed by expanding traditional line switching with breaker-level bus splitting, which can further reduce grid congestion and generation costs. A tight McCormick relaxation is proposed to reformulate the bi-linear terms in the resultant topology optimization model. Thus, a tractable mixed-integer linear program formulation is presented which can be efficiently solved for real-time control. Numerical studies on the IEEE 14-bus and 118-bus systems demonstrate the performance and economic benefits of the proposed topology optimization approach.

bus split↗
DOE OSTI2021

CATMoS: Collaborative Acute Toxicity Modeling Suite

Background: Humans are exposed to tens of thousands of chemical substances that need to be assessed for their potential toxicity. Acute systemic toxicity testing serves as the basis for regulatory hazard classification, labeling, and risk management. However, it is cost- and time-prohibitive to evaluate all new and existing chemicals using traditional rodent acute toxicity tests. In silico models built using existing data facilitate rapid acute toxicity predictions without using animals. Objectives: The U.S. Interagency Coordinating Committee on the Validation of Alternative Methods Acute Toxicity Workgroup organized an international collaboration to develop in silico models for predicting acute oral toxicity based on five different endpoints: LD50 value, U.S. Environmental Protection Agency hazard categories, Globally Harmonized System for Classification and Labelling hazard categories, very toxic chemicals (LD50 =50 mg/kg), and non-toxic chemicals (LD50 >2000 mg/kg). Methods: An acute oral toxicity data inventory for 11,992 chemicals was compiled, split into training and evaluation sets, and made available to 35 participating international research groups that submitted a total of 139 predictive models. Predictions that fell within the applicability domains of the submitted models were evaluated using external validation sets. These were then combined into consensus models to leverage strengths of individual approaches. Results: The resulting consensus predictions, which leverage the collective strengths of each individual model, form the Collaborative Acute Toxicity Modeling Suite (CATMoS). CATMoS demonstrated high performance in terms of accuracy and robustness when compared to in vivo results. Discussion: CATMoS is being evaluated by regulatory agencies for its utility and applicability as a potential replacement for in vivo rat acute oral toxicity studies. CATMoS predictions for over 800,000 chemicals have been made available via the NTP’s Integrated Chemical Environment. The models are also implemented in a free, standalone open-source tool, OPERA, which allows predictions of new and untested chemicals to be made.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2019

A Proposal of Conducting Bioequivalence Trials with Gastric pH Modulators for Two Oral Formulations Demonstrating Different Dissolution Profiles at Elevated pH

In this paper, a special case for bioequivalence evaluation of oral formulations is discussed. Drug formulations with different forms of active moieties (e.g., free base and salt) may yield different dissolution characteristics and, thus, differ in absorption at elevated gastric pH . However, routine bioequivalence trials using subjects with normal gastric pH (i.e., ~ 1) may fail to identify these differences because dissolution/absorption profiles of the two formulations at normal gastric pH are similar. In the case of palbociclib, it is confirmedthat the free base and salt formulations showed different absorption in patients with different gastric pH . Significant reduction in drug absorption was observed only in patients with elevated gastric pH using free base formulation. The discovery that the free base had significantly reduced absorption hinged on the inclusion of enough patients with elevated gastric pH to detect a difference in a bioequivalence trial. This raises a concern, as demonstrated through simulation, that dissolution/absorption differences in other formulations could be missed in routine bioequivalence trials. Aside from differences in active pharmaceutical ingredients ( API s), other factors, such as changes in excipients or manufacturing methods, may also lead to exposure differences between formulations at elevated gastric pH . For formulations containing different forms of the same active moiety or the same API and showing different dissolution profiles at elevated pH (i.e., pH ~ 4–6.8), evaluation of bioequivalence with gastric pH modulators (e.g., a H 2 blocker) in addition to routine bioequivalence assessments may help to ensure therapeutic equivalence in patients with elevated gastric pH .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Mitotic regulators and the SHP2-MAPK pathway promote IR endocytosis and feedback regulation of insulin signaling

Insulin controls glucose homeostasis and cell growth through bifurcated signaling pathways. Dysregulation of insulin signaling is linked to diabetes and cancer. The spindle checkpoint controls the fidelity of chromosome segregation during mitosis. Here, we show that insulin receptor substrate 1 and 2 (IRS1/2) cooperate with spindle checkpoint proteins to promote insulin receptor (IR) endocytosis through recruiting the clathrin adaptor complex AP2 to IR. A phosphorylation switch of IRS1/2 orchestrated by extracellular signal-regulated kinase 1 and 2 (ERK1/2) and Src homology phosphatase 2 (SHP2) ensures selective internalization of activated IR. SHP2 inhibition blocks this feedback regulation and growth-promoting IR signaling, prolongs insulin action on metabolism, and improves insulin sensitivity in mice. We propose that mitotic regulators and SHP2 promote feedback inhibition of IR, thereby limiting the duration of insulin signaling. Targeting this feedback inhibition can improve insulin sensitivity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Dynamic Power Distribution System Management With a Locally Connected Communication Network

Coordinated optimization and control of distribution-level assets can enable a reliable and optimal integration of massive amount of distributed energy resources (DERs) and facilitate distribution system management (DSM). Accordingly, the objective is to coordinate the power injection at the DERs to maintain certain quantities across the network, e.g., voltage magnitude, line flows, or line losses, to be close to a desired profile. By and large, the performance of the DSM algorithms has been challenged by two factors: i) the possibly non-strongly connected communication network over DERs that hinders the coordination; ii) the dynamics of the real system caused by the DERs with heterogeneous capabilities, time-varying operating conditions, and real-time measurement mismatches. In this paper, we investigate the modeling and algorithm design and analysis with the consideration of these two factors. In particular, a game theoretic characterization is first proposed to account for a locally connected communication network over DERs, along with the analysis of the existence and uniqueness of the Nash equilibrium (NE) therein. To achieve the equilibrium in a distributed fashion, a projected-gradient-based asynchronous DSM algorithm is then advocated. The algorithm performance, including the convergence speed and the tracking error, is analytically guaranteed under the dynamic setting. In conclusion, extensive numerical tests on both synthetic and realistic cases corroborate the analytical results derived.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Analytic Considerations and Design Basis for the IEEE Distribution Test Feeders

One of the greatest challenges for the analysis of distribution systems is the high level of diversity across the world. For nearly 20 years the Test Feeder Working Group of the Distribution System Analysis Subcommittee has been developing distribution test feeders. The purpose of these test feeders is to provide openly-available models of distribution systems that reflect the diversity in systems and the analytic challenges they present. Because of their utility and accessibility, the test feeders have been used for a wide range of research, some of which they were not originally intended to cover. The purpose of this paper is to provide an overview of the variety of existing distribution systems, and to clarify the specific analytic challenges that each test feeder was originally designed to examine. Additionally, the paper will provide guidance on which feeders are best suited for various types of analysis. The purpose of this paper is to provide the original intent of the Working Group and to inform researchers so that they may make an informed decision on which of the test feeders are most appropriate for their work.

Schneider, Kevin P.↗
DOE OSTI2017

Toward a systematic exploration of nano-bio interactions

Many studies of nanomaterials make non-systematic alterations of nanoparticle physicochemical properties. Given the immense size of the property space for nanomaterials, such approaches are not very useful in elucidating fundamental relationships between inherent physicochemical properties of these materials and their interactions with, and effects on, biological systems. Data driven artificial intelligence methods such as machine learning algorithms have proven highly effective in generating models with good predictivity and some degree of interpretability. They can provide a viable method of reducing or eliminating animal testing. However, careful experimental design with the modelling of the results in mind is a proven and efficient way of exploring large materials spaces. This approach, coupled with high speed automated experimental synthesis and characterization technologies now appearing, is the fastest route to developing models that regulatory bodies may find useful. We advocate greatly increased focus on systematic modification of physicochemical properties of nanoparticles combined with comprehensive biological evaluation and computational analysis. This is essential to obtain better mechanistic understanding of nano-bio interactions, and to derive quantitatively predictive and robust models for the properties of nanomaterials that have useful domains of applicability. - Highlights: • Nanomaterials studies make non-systematic alterations to nanoparticle properties. • Vast nanomaterials property spaces require systematic studies of nano-bio interactions. • Experimental design and modelling are efficient ways of exploring materials spaces. • We advocate systematic modification and computational analysis to probe nano-bio interactions.

60 APPLIED LIFE SCIENCES↗