An activity-based spatial-temporal community electricity vulnerability assessment framework

The power system is among the most important critical infrastructures in urban cities and is getting increasingly essential in supporting people s daily activities. However, it is also susceptible to most natural disasters such as tsunamis, floods, or earthquakes. Electricity vulnerability, therefore, forms a crucial basis for community resilience. This paper aims to present an assessment framework of spatial-temporal electricity vulnerability to support the building of community resilience against power outages. The framework includes vulnerability indexes in terms of occupant demographics, occupant activity patterns, and urban building characteristics. To integrate factors in these aspects, we also proposed a process as activity simulation-mapping-evaluation-visualization to apply the framework and visualize results. This framework can help planners make an effective first-time response by identifying the most vulnerable areas when a massive power outage happens during natural disasters. It can also be integrated into community resilience analysis models and potentially contributes to effective disaster risk managementComment: to be published in Proceedings of the 5th International Conference on Building Energy and Environmen

Community Time-Activity Trajectory Modelling based on Markov Chain Simulation and Dirichlet Regression

Accurate modeling of human time-activity trajectory is essential to support community resilience and emergency response strategies such as daily energy planning and urban seismic vulnerability assessment. However, existing modeling of time-activity trajectory is only driven by socio-demographic information with identical activity trajectories shared among the same group of people and neglects the influence of the environment. To further improve human time-activity trajectory modeling, this paper constructs community time-activity trajectory and analyzes how social-demographic and built environment influence people s activity trajectory based on Markov Chains and Dirichlet Regression. We use the New York area as a case study and gather data from American Time Use Survey, Policy Map, and the New York City Energy & Water Performance Map to evaluate the proposed method. To validate the regression model, Box s M Test and T-test are performed with 80% data training the model and the left 20% as the test sample. The modeling results align well with the actual human behavior trajectories, demonstrating the effectiveness of the proposed method. It also shows that both social-demographic and built environment factors will significantly impact a community's time-activity trajectory. Specifically, 1) Diversity and median age both have a significant influence on the proportion of time people assign to education activity. 2) Transportation condition affects people s activity trajectory in the way that longer commute time decreases the proportion of biological activity (eg. sleeping and eating) and increases people s working time. 3) Residential density affects almost all activities with a significant p-value for all biological needs, household management, working, education, and personal preference.Comment: to be published in Computers, Environment and Urban Syste

Taxonomy, Semantic Data Schema, and Schema Alignment for Open Data in Urban Building Energy Modeling

Urban Building Energy Modeling (UBEM) is a critical tool to provide quantitative analysis on building decarbonization, sustainability, building-to-grid integration, and renewable energy applications on city, regional, and national scales. Researchers usually use open data as inputs to build and calibrate UBEM. However, open data are from thousands of sources covering various perspectives of weather, building characteristics, etc. Besides, a lack of semantic features of open data further increases the engineering effort to process information to be directly used for UBEM as inputs. In this paper, we first reviewed open data types used for UBEM and developed a taxonomy to categorize open data. Based on that, we further developed a semantic data schema for each open data category to maintain data consistency and improve model automation for UBEM. In a case study, we use three popular open data to show how they can be automatically processed based on the proposed schematic data structure using large language models. The accurate results generated by large language models indicate the machine-readability and human-interpretability of the developed semantic data schema

Accuracy Analysis of Attitude Computation Based on Optimal Coning Algorithm

To accurately evaluate the applicability of optimal coning algorithms, the direct influence of their periodic components on attitude accuracy is investigated. The true value of the change of the rotation vector is derived from the classical coning motion for analytic comparison. The analytic results show that the influence of periodic components is mostly dominant in two types of optimal coning algorithms. Considering that the errors of periodic components cannot be simply neglected, these algorithms are categorized with simplified forms. A variety of simulations are done under the classical coning motion. The numerical results are in good agreement with the analytic deductions. Considering their attitude accuracy, optimal coning algorithms of the 4-subinterval and 5-subinterval algorithms optimized with angular increments are not recommended for use for real application.Defence Science Journal, 2012, 62(6), pp.361-368, DOI:http://dx.doi.org/10.14429/dsj.62.143

Analytical Solution of Poisson's Equation with Application to VLSI Global Placement

Poisson's equation has been used in VLSI global placement for describing the potential field caused by a given charge density distribution. Unlike previous global placement methods that solve Poisson's equation numerically, in this paper, we provide an analytical solution of the equation to calculate the potential energy of an electrostatic system. The analytical solution is derived based on the separation of variables method and an exact density function to model the block distribution in the placement region, which is an infinite series and converges absolutely. Using the analytical solution, we give a fast computation scheme of Poisson's equation and develop an effective and efficient global placement algorithm called Pplace. Experimental results show that our Pplace achieves smaller placement wirelength than ePlace and NTUplace3. With the pervasive applications of Poisson's equation in scientific fields, in particular, our effective, efficient, and robust computation scheme for its analytical solution can provide substantial impacts on these fields

A Study of Self-Burial of a Radioactive Waste Container by Deep Rock Melting

Aiming at the problem of radioactive waste disposal, the concept and mechanism of self-burial by deep rock melting are presented. The rationality and feasibility of self-burial by deep rock melting are analyzed by comparing with deep geological burial. The heat threshold during the process of contact melting around a spherical heat source is defined. The descent velocities and burial depths of spherical waste containers with varying radius are calculated. The calculated depth is much smaller than that obtained in the related literature. The scheme is compared with the deep geological burial that is currently carried out by the main nuclear countries. It is found that, at the end of melting, a radioactive waste container can reach deep strata that are isolated from groundwater

Hydrodeoxygenation of Methyl Laurate over Ni Catalysts Supported on Hierarchical HZSM-5 Zeolite

The hierarchical HZSM-5 zeolite was prepared successfully by a simple NaOH treatment method. The concentration of NaOH solution was carefully tuned to optimal the zeolite acidity and pore structure. Under NaOH treatment conditions, a large number of mesopores, which interconnected with the retained micropores, were created to facilitate mass transfer performance. There are very good correlations between the decline of the relative zeolite crystallinity and the loss of micropores volume. The Ni nanoclusters were uniformly confined in the mesopores of hierarchical HZSM-5 by the excessive impregnation method. The direct deoxygenation in N2 and hydrodeoxygenation in H2 of the methyl laurate were compared respectively over the Ni/HZSM-5 catalysts. In the N2 atmosphere, the deoxygenation rate of the methyl laurate on the Ni/HZSM-5 catalyst is relatively slow. In the presence of H2, the synergistic effect between the hydrogenation function of the metal and the acid function of the zeolite supports can make the deoxygenation level more obvious. The yield of hydrocarbon products gradually reached the maximum with the appropriate treatment concentration of 1M NaOH, which could be attributed to the improved mass transfer in the hierarchical HZSM-5 supports