Planning Framework Research Articles

Synergistic assessment of multi-scenario urban waterlogging through data-driven decoupling analysis in high-density urban areas: A case study in Shenzhen, China

Extreme meteorological events and rapid urbanization have led to serious urban flooding problems. Characterizing spatial variations in flooding susceptibility and elucidating its driving factors are essential for preventing damages from urban pluvial flooding. However, conventional methods, limited by spatial heterogeneity and the intricate mechanisms of urban flooding, frequently demonstrated a deficiency in precision when assessing flooding susceptibility in dense urban areas. Therefore, this study proposed a novel framework for an integrated assessment of urban flood susceptibility, based on a comprehensive cascade modeling chain consisting of XGBoost, SHapley Additive exPlanations (SHAP), and Partial Dependence Plots (PDP) in combination with K-means. It aimed to recognize the specific influence of urban morphology and the spatial patterns of flooding risk agglomeration under different rainfall scenarios in high-density urban areas. The XGBoost model demonstrated enhanced accuracy and robustness relative to other three benchmark models: RF, SVR, and BPDNN. This superiority was effectively validated during both training and independent testing in Shenzhen. The results indicated that urban 3D morphology characteristics were the dominant factors for waterlogging magnitude, which occupied 46.02 % of relative contribution. Through PDP analysis, multi-staged trends highlighted critical thresholds and interactions between significant indicators like building congestion degree (BCD) and floor area ratio (FAR). Specifically, optimal intervals like BCD between 0 and 0.075 coupled with FAR values between 0.5 and 1 have the potential to substantially mitigate flooding risks. These findings emphasize the need for strategic building configuration within urban planning frameworks. In terms of the spatial-temporal assessment, a significant aggregation effect of high-risk areas that prone to prolonged duration or high-intensity rainfall scenarios emerged in the old urban districts. The approach in the present study provides quantitative insights into waterlogging adaptation strategies for sustainable urban planning and design.

A novel framework for production planning and class-based storage location assignment: Multi-criteria classification approach

Efficient warehouse management is essential for optimizing inventory, minimizing transportation costs, and enhancing overall performance. This research introduces a novel Mixed-Integer Nonlinear Programming (MINLP) model to address the Storage Location Assignment Problem (SLAP) in warehouse management. Integrating multi-criteria decision-making with strategic production planning, our model advances warehouse operations by allocating storage locations to products strategically, focusing on reducing transportation distances and maximizing storage efficiency. The distinctive innovation of this study is the nuanced application of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) results to strategic storage location assignments, enhancing the model's capability to consider a comprehensive evaluation of inventory attributes, including physical characteristics and perishability. This approach evolves TOPSIS's application in warehouse management, enabling it to consider both physical characteristics and perishability of products. The outcomes of TOPSIS, including product classifications and preferences, serve as vital inputs to the mathematical model, facilitating a comprehensive evaluation of storage locations that encompasses spatial, demand-related, and physical aspects of inventory. Additionally, our research introduces a versatile decision support system, adaptable to various operational requirements. This system enhances practical decision-making in warehouse management, accommodating scenarios based on single or multiple criteria, including the cube-per-order index (COI). The research results highlight the significant impact of this innovative approach in enhancing warehouse management. By addressing the complexities of storage location assignment and integrating multiple criteria, we achieve more efficient and cost-effective warehouse operations. The approach has been shown to be adaptable and practical, making it a valuable contribution to the field of logistics and warehouse management.

Neoliberal urban segregation and property tax: A critical view of Santiago, Chile

Urban property taxes are primordial land value capture mechanisms that can potentially redistribute public income to underprivileged areas in a city. However, in Santiago, Chile, a city with considerable socio-spatial segregation correlated with significant disparities in municipal budgets, social welfare, and intergenerational reproduction of wealth, the property tax system is weak to address this issue effectively. This study analyses the potential redistributive capacity of property taxes in Greater Santiago, comparing the evolution of real estate surplus values with municipal budgets. These results show that a 2% increase in property taxes would suffice to equalize per capita municipal budgets, essential to redistribute social welfare. In Chiles’s neoliberal planning framework, we argue that weak property taxes are critical for the intergenerational reproduction of wealth and poverty in different municipalities. Property as capital is efficient for capturing unearned value in the long term and obtaining rental income, two mechanisms of inequality reproduction, as property accumulation is only feasible if it is not progressively taxed. In sum, this analysis of property taxes in Santiago contributes to the theoretical understanding of passive mechanisms of inequality reproduction in a neoliberal system and empirical support for a progressive increase of property taxes.

PERSPECTIVE: Cryosurgery process applications: a mathematical review

The present study reviews some of the prominent mathematical models that are used to simulate the cryosurgery treatment of tumor tissues, i.e., destruction of tumor tissues via controlled freezing with cryoprobes with minimizing the impact on surrounding healthy tissues. Numerical simulation of the appropriate mathematical models that reflect practical situations may help the physicians to design a planning framework for the treatment, which includes total number of cryoprobes to be used, their placement design and the duration of optimal freezing, etc. Finite element method, meshfree method, and finite volume method are some of the suitable numerical techniques for simulating bio-heat transfer process within complex tissues during treatment.

Reorientation of energy policy and management: Integrated Energy Planning (IEP) framework implementation for Renewable and Thermal Energy Systems (RTES)

To bridge the critical implementation gap in Renewable and Thermal Energy Systems (RTES) sector, this study proposed a groundbreaking Integrated Energy Planning (IEP) framework. Existing policy analysis methods for RTES often fall short. This limitation was addressed by investigating the disconnect between policy vision and execution within intricate energy landscape. This analysis was extended beyond Pakistan, incorporating energy policies from leading developed and developing nations alongside a comprehensive existing energy modeling efforts for RTES. By leveraging these insights, the potential of IEP was demonstrated to account for trade-offs and seamlessly integrate diverse energy sources. This paves the way for a more sustainable, secure, and efficient RTES for future.

A Mobility Justice Framework to prioritize areas for mobility interventions

Understanding, visualizing, and quantifying how resources are allocated and the fairness of distributions and access is significant for supporting decision-makers in incentivizing development and ensuring that future changes are widely beneficial and fair. By pointing out the need for mobility justice research to shift from state-centric to more society-centric frameworks and metrics, this study proposed a Mobility Justice Framework that integrated two important theories of justice: distribution and recognition justice. The proposed framework highlights the distribution of amenities and burdens in providing transport infrastructure. It also aims to identify those disadvantaged socio-economic groups more exposed to mobility inequalities. To make the framework applicable within the city context and guide decision-making, several metrics (variables) were identified to make principles of distributive and recognition justice operationalizable. Variables such as 1) accessibility by walking, 2) exposure to traffic negative effects, 3) frequency of use of transport modes, and 4) availability of transport infrastructure were used to identify neighborhoods and the different types of mobility resources/burdens that disadvantaged socio-economic groups are exposed to. To showcase its usability, the framework and methodology have been applied to the city of Munich to highlight neighborhoods with a higher proportion of older people and the transport disadvantages associated with these target groups. A higher negative correlation between older people and mobility resources/burdens can be observed for the following variables: accessibility by walking to activities, availability of walking and cycling infrastructure, and availability of car-sharing services. When measured against exposure to negative transport effects, a higher positive correlation was observed. The paper ends with a discussion section on the relevance and usability of the proposed framework for transport planning and policy and its limitations.

Strategies for Land Economic Development in South Delhi District

This research paper examines the land economic development strategies in South Delhi, focusing on their impact on the socio-economic and spatial dynamics of the region. South Delhi, a diverse and economically vibrant district within the National Capital Region of India, presents a unique case study to explore how tailored land use policies and economic planning can foster sustainable growth. Using a mixed-method approach, this study integrates qualitative analysis of policy documents, stakeholder interviews, and quantitative assessment of economic indicators to analyze land use changes, economic transformations, and policy effectiveness from 2011 to 2021. The analysis spans both macro and micro levels, investigating transformations in key areas like Mehrauli, Lado Sarai, and Aya Nagar. Findings highlight significant shifts in land use from agricultural to residential and commercial purposes, driven by rapid urbanization, infrastructure development, and policy reforms. While certain strategies have effectively promoted economic growth, challenges such as environmental degradation, congestion, uneven policy enforcement, and socio- economic disparities persist. The study underscores the need for sustainable land use planning, improved infrastructure, stakeholder collaboration, and adaptive governance frameworks to balance economic growth with social equity and environmental sustainability The research offers comprehensive insights and practical recommendations for policymakers, urban planners, and stakeholders to optimize land economic development strategies in South Delhi, with implications for similar urban contexts globally. The study advocates for a holistic approach that integrates sustainable development, community engagement, and resilient policy frameworks to create livable and prosperous urban environments. Index Terms— Land Economic Development Strategies,South Delhi, Socio-Economic Dynamics ,Spatial Dynamics, Land Use Policies ,Economic Planning ,Sustainable Growth ,Mixed-Method Approach, Policy Documents, Stakeholder Interviews, Economic Indicators, Land Use Changes, Urbanization, Infrastructure Development ,Policy Reforms Environmental Degradation, Socio- Economic Disparities ,Sustainable Land Use Planning, Stakeholder Collaboration, Adaptive Governance, Urban Environments.

Maximum Self-Consumption Planning Framework Considering Energy Management System for Optimal Photovoltaic-Battery System in Distribution Network

Power production from photovoltaic (PV) has advanced as Renewable Energy Resources (RES) power technology and is now a worthwhile alternative to conventional power generating. To effectively stabilize the process of connecting to the grid and increase power controllability owing to changing PV power production, energy storage systems (ESS), with their flexible charging and discharging capabilities, are most often used to cooperate with RES power generation. However, ESS's rapid rate of charging and discharging might cause it to age more quickly than it should and reduce its lifespan. Therefore, this study proposed an effective planning framework of optimal penetration of PV-ESS system associated with effective energy management systems (EMS). The proposed framework, the optimal PV size, PV location and maximum State of Charge (SOCmax) are determined. The fixed minimum State of Charge (SOCmin) based on load conditions is applied to minimize the degradation while maximizing PV self-consumption. The result shows that when applying different SOCmin during at off-peak and peak time load demand, the degradation cost is reduced to 19.40%.

Developing an optimization framework for capacity planning of hydrogen-based residential energy hub

— This paper introduces a comprehensive modeling approach for optimizing the capacities of various energy converters and storage systems within a residential Energy Hub (EH). The model focuses on minimizing energy supply costs to customers while maximizing the utilization of renewable and hydrogen-based technologies. Through the optimization process, we determined that implementing CHP units in the EH could reduce total costs by approximately 78% with green tax incentives and by 46.7% without them. Additionally, the inclusion of an incentive to the EH resulted in a 27.2% reduction in total costs imposed on subscribers.The study also evaluates the impact of uncertainties in photovoltaic (PV) electricity generation, demonstrating the benefits of using stochastic optimization over deterministic methods. The results indicate that the economic advantage of this approach over deterministic methods is 86.75%–95.74% greater, depending on the scenario. Sensitivity analysis further reveals that the investment costs of fuel cells significantly influence the optimal capacity design and economic viability of the EH model.

Robust Path Planning via Learning from Demonstrations for Robotic Catheters in Deformable Environments.

Navigation through tortuous and deformable vessels using catheters with limited steering capability underscores the need for reliable path planning. State-of-the-art path planners do not fully account for the deformable nature of the environment. This work proposes a robust path planner via a learning from demonstrations method, named Curriculum Generative Adversarial Imitation Learning (C-GAIL). This path planning framework takes into account the interaction between steerable catheters and vessel walls and the deformable property of vessels. In-silico comparative experiments show that the proposed network achieves a 38% higher success rate in static environments and 17% higher in dynamic environments compared to a state-of-the-art approach based on GAIL. In-vitro validation experiments indicate that the path generated by the proposed C-GAIL path planner achieves a targeting error of 1.26 ±0.55mm and a tracking error of 5.18 ±3.48mm. These results represent improvements of 41% and 40% over the conventional centerline-following technique for targeting error and tracking error, respectively. The proposed C-GAIL path planner outperforms the state-of-the-art GAIL approach. The in-vitro validation experiments demonstrate that the path generated by the proposed C-GAIL path planner aligns better with the actual steering capability of the pneumatic artificial muscle-driven catheter utilized in this study. Therefore, the proposed approach can provide enhanced support to the user in navigating the catheter towards the target with greater accuracy, effectively meeting clinical accuracy requirements. The proposed path planning framework exhibits superior performance in managing uncertainty associated with vessel deformation, thereby resulting in lower tracking errors.

FLUENT: Towards a more flexible design and planning approach

The following paper introduces the FLUENT model, a contemporary university course planning approach built on the findings from a research which used the results of a survey, interviews to university key informants and a literature review based on the PRISMA methodology. FLUENT is an acronym that stands for Flexible Universal Education Model for a New Hybrid. Faced with the complexity of teaching and uncertainty in planning, the model aims to comprehensively address course planning intricacies. Unlike traditional models, FLUENT adopts a fully online perspective, acknowledging the potential of online education. It incorporates evidence-backed elements from course design, as for example emphasizing deep understanding, accurate planning, or crucial structuring elements. The structuring elements encompass time, space, technology, students' agency, and teachers' reflectivity. Additionally, FLUENT integrates principles of reversibility, addressing unforeseen circumstances, and recognizes students in both face-to-face and online environments. The model promotes flexibility, personalization, interaction, and collaboration, aligning with the pillars of future learning. FLUENT stands out by offering reversible design, considering diverse needs of students, and being adaptable to diverse institutional infrastructures. The model emphasizes learning paths, competencies, and aligning objectives, providing a comprehensive framework for course planning.

Barriers, Challenges, and Opportunities in the Adoption of the Circular Economy in Mexico: An Analysis through Social Perception

This study explores the transition toward sustainable economic models through the circular economy (CE) in Mexico. Utilizing a mixed-methods approach, this research incorporates a comprehensive literature review and analyzes responses from 42 stakeholders, gathered through surveys and focus groups. These stakeholders comprise a diverse group including PhD students, professors, researchers, industry professionals in sustainability and the environment, and government advisors and coordinators from the Mexican Secretary of Environment. This representative sample provides a broad perspective on the barriers, opportunities, and societal perceptions regarding CE. The findings reveal significant challenges such as economic barriers, regulatory inadequacies, and a lack of awareness and education, all of which hinder the adoption of CE practices. Despite these challenges, there is a generally optimistic view among stakeholders about CE’s potential to positively impact societal needs, suggesting robust opportunities for innovation and policy enhancement to foster sustainable development. Key recommendations include intensifying educational programs to elevate public understanding and engagement, formulating supportive policies that facilitate CE adoption, and promoting intersectoral collaboration to leverage collective expertise and resources. Additionally, the research underscores the necessity of integrating CE principles into urban planning and policy frameworks to effectively address specific local challenges such as waste management, pollution, and urban sprawl. By providing a detailed analysis of the current state and potential of CE in Mexico, this paper contributes valuable insights to the global discourse on sustainability. It proposes strategic actions to overcome existing hurdles and capitalize on opportunities within the CE framework, charting a path forward for Mexico and serving as a model for other regions facing similar sustainability challenges

Geospatial Point-of-Care Testing Strategies for COVID-19 Resilience in Resource-Poor Settings: Rural Cambodia Field Study.

Point-of-care testing (POCT) generates intrinsically fast, inherently spatial, and immediately actionable results. Lessons learned in rural Cambodia and California create a framework for planning and mobilizing POCT with telehealth interventions. Timely diagnosis can help communities assess the spread of highly infectious diseases, mitigate outbreaks, and manage risks. The aims of this study were to identify the need for POCT in Cambodian border provinces during peak COVID-19 outbreaks and to quantify geospatial gaps in access to diagnostics during community lockdowns. Data sources comprised focus groups, interactive learners, webinar participants, online contacts, academic experts, public health experts, and officials who determined diagnostic needs and priorities in rural Cambodia during peak COVID-19 outbreaks. We analyzed geographic distances and transit times to testing in border provinces and assessed a high-risk province, Banteay Meanchey, where people crossed borders daily leading to disease spread. We strategized access to rapid antigen testing and molecular diagnostics in the aforementioned province and applied mobile-testing experience among the impacted population. COVID-19 outbreaks were difficult to manage in rural and isolated areas where diagnostics were insufficient to meet needs. The median transit time from border provinces (n=17) to testing sites was 73 (range 1-494) minutes, and in the high-risk Banteay Meanchey Province (n=9 districts), this transit time was 90 (range 10-150) minutes. Within border provinces, maximum versus minimum distances and access times for testing differed significantly (P<.001). Pareto plots revealed geospatial gaps in access to testing for people who are not centrally located. At the time of epidemic peaks in Southeast Asia, mathematical analyses showed that only one available rapid antigen test met the World Health Organization requirement of sensitivity >80%. We observed that in rural Solano and Yolo counties, California, vending machines and public libraries dispensing free COVID-19 test kits 24-7 improved public access to diagnostics. Mobile-testing vans equipped with COVID-19 antigen, reverse transcription polymerase chain reaction, and multiplex influenza A/B testing proved useful for differential diagnosis, public awareness, travel certifications, and telehealth treatment. Rural diagnostic portals implemented in California demonstrated a feasible public health strategy for Cambodia. Automated dispensers and mobile POCT can respond to COVID-19 case surges and enhance preparedness. Point-of-need planning can enhance resilience and assure spatial justice. Public health assets should include higher-quality, lower-cost, readily accessible, and user-friendly POCT, such as self-testing for diagnosis, home molecular tests, distributed border detection for surveillance, and mobile diagnostics vans for quick telehealth treatment. High-risk settings will benefit from the synthesis of geospatially optimized POCT, automated 24-7 test access, and timely diagnosis of asymptomatic and symptomatic patients at points of need now, during new outbreaks, and in future pandemics.

Are we going towards an effective integration of air quality and climate planning? A comparative analysis for Italian regions

Climate change mitigation and adaptation along with air pollution are key challenges that require a comprehensive planning approach able to promote win-win strategies and avoid transferring environmental pressures from one sector to another. The joint approach is widely advocated at the policy level while the scientific research investigates the role of co-benefits in planning processes. A methodological framework was developed with the twofold aim of (i) assessing the current integration degree between regional Air Quality Plans and Climate Plans and (ii) providing useful hints for pursuing greater air-climate integration. Its application to the Italian case study provides useful policy implications for strengthening the role of co-benefits as drivers of planning processes. Results show that a greater air-climate integration can be achieved by enhancing the role of regional authorities in supporting the implementation of local-scale plans and actions. This is especially important in contexts where an integrated planning framework is lacking and the mainstreaming within sectoral sub-regional plans turns out to be crucial.

Can we stop reinventing the wheel in blue-green infrastructure planning? Using value-focused thinking to enable transferability of a multicriteria planning support system

Strategic planning approaches are essential for addressing the complex and multi-dimensional challenges in selecting blue-green infrastructure (BGI) location. The development of planning support systems (PSS) for BGI siting often lacks a value-based approach with early stakeholder engagement. In this study, we used value-focused thinking (VFT) to adapt and develop a BGI planning support framework to the Canadian urban context, moving towards an objective-driven framework. We provide a hierarchical objectives framework for BGI planning in urban areas, aligned with stakeholder values, with three-level information: higher-level objectives, lower-level objectives and measurable spatial attributes. To assess site performance across these attributes, value scales elicitation was conducted with 17 experts. The engagement of 37 stakeholders in co-creating and validating our objectives set helped identify common concerns and refine our framework, focusing on the most relevant objectives for stakeholders. The VFT approach and the resulting framework can be easily transferred to other cities in Quebec (Canada), but also to other urban contexts looking to optimize BGI site selection to maximize benefits across the multiple functions of BGI and opportunities arising from the urban context.

An innovative integrated framework for multi-level production planning and control systems in construction

The construction industry is plagued by chronic inefficiencies, such as low productivity, significant waste, cost overruns, and schedule delays. One of the most critical contributors to these issues is fragmented and ineffective planning and control methods. This research aims to address these challenges by developing an innovative integrated multi-level framework for production planning and control that harmonizes various planning methods and control metrics across different schedule levels. Employing the Design Science Research (DSR) methodology, this study systematically develops and evaluates an innovative framework that integrates internal and external project characteristics, utilizing the concept of "functionality" as a primary key for coherent integration. Furthermore, a multi-objective mathematical model is incorporated to clarify the framework's components and optimize the number of suggested planning methods and control metrics at each scheduling level, aiming to balance the functional requirements of project teams with the practicality of implementation.The application of the framework to a renovation case study demonstrates its practicality and strategic value, effectively addressing real-world project management challenges. Moreover, industry and academic evaluations highlight its potential to significantly improve construction project management practices.

A framework for integrated resource planning in surgical clinics

The problem under study is based on the challenges faced by the Orthopaedic Clinic at St. Olav’s Hospital in Trondheim, Norway. Variations in demand and supply cause fluctuating waiting lists, and it is challenging to level the activities between the clinic’s two units, the outpatient clinic and the operating theater, to obtain short waiting times for all activities. Based on these challenges, we describe and present a planning problem referred to as the Long-term Master Scheduling Problem (LMSP), where the objective is to construct an integrated Long-term Master Schedule (LMS) that facilitates short waiting times in both units. The LMS can be separated into two schedules, one cyclic high-level schedule, and one non-cyclic low-level schedule. The demand for outpatient clinic consultations and surgeries is stochastic, as are the waiting lists. To account for this, we propose a planning framework consisting of an optimization model to solve the LMSP, and a two-level planning procedure. In the planning procedure, we first solve the LMSP to construct the LMS for the upcoming planning horizon. Then, to adjust to the fluctuating waiting lists, we periodically refine the low-level schedule by solving a constrained LMSP. We also develop a simulation-based evaluation procedure to evaluate the planning framework in a real-life setting and use this to investigate different planning strategies. We find that imposing flexible, dynamic and agile planning strategies improve waiting time outcomes and patient throughput. Furthermore, combining the strategies yields additive improvements.

Gender-inclusive urban planning: European frameworks as a potential methodology for Arabian Gulf urban parks

PurposeThis trigger article explores established European gender-mainstreaming urban planning frameworks of urban parks to analyze and identify ways that could be applied or adapted for Arabian Gulf cities. It aims to accelerate the mainstreaming process, increasing women’s participation and inclusion in urban spaces, paving the way for future research.Design/methodology/approachAnalytical frameworks are created by reviewing legal and policy evolution, city-issued guidelines and European cities’ case studies (Barcelona, Berlin, Paris and Vienna) engaged in gender mainstreaming in urban planning. These analytical tools are then applied to assess two Arabian Gulf parks (Al Azaiba Wadi Park, Muscat, Oman, and Dahl Al-Hamam Park, Doha, Qatar), suggesting a possible future research methodology.FindingsSuccess factors in European cities include integrating female perspectives, detailed user analysis, specific planning solutions and political will. Despite differing social and cultural contexts, commonalities exist for female park users in Europe and the Arabian Gulf. This trigger article proposes a methodology for assessing the potential effective application or adaptation of European established frameworks in the Gulf context to accelerate gender mainstreaming.Research limitations/implicationsThe paper proposes a methodology for future research, noting limitations such as limited input on design preparation processes in Gulf City park case studies, a lack of feedback from park users and only a brief overview of sociocultural differences. Future research should explore nuanced cultural contexts, including historical processes and gender dynamics, thorough literature review, expanded case study analysis and participatory approaches. The proposed methodology aims to demonstrate how European frameworks can guide gender-mainstreaming efforts in diverse contexts, facilitating collaborative solutions for inclusive urban planning.Practical implicationsDrawing from decades of European gender-mainstreaming activities, the paper distills urban planning principles and best practices for application or adaptation in the Arab Gulf.Social implicationsEnhancing the park experience for women through planning and design boosts gender equality in cities, benefiting their physical and social well-being.Originality/valueAn original methodology is suggested for adapting well-developed European gender-mainstreaming frameworks to Arabian Gulf parks. Authored by a male, this paper aims to advance gender issues in planning while exploring the role men can play in contributing to such.

A Vehicle-to-Grid planning framework incorporating electric vehicle user equilibrium and distribution network flexibility enhancement

The rapid surge in electric vehicle (EV) adoption, coupled with advancements in charging technologies, emphasizes the critical necessity for expanding EV recharging infrastructure. Simultaneously, the Distribution Network (DN) encounters escalating challenges in meeting charging demand during peak traffic periods. Consequently, there is a mounting demand for the deployment of innovative Vehicle-to-Grid (V2G) technologies to augment the DN’s flexibility in power dispatch and alleviate travel costs for EV users. Hence, this paper proposes an EV-user-equilibrium-(UE)-constrained V2G planning framework that enhances flexibility in the DN. The framework aims to ascertain the optimal placement and capacity of EV charging stations (EVCSs) and V2G charging piles within the Transportation Network (TN). It takes into account the equilibrium condition stemming from competitive EV charging and routing behaviors alongside the optimal expansion of DN energy resources to accommodate the electricity supplied by the V2G piles. This study commences by analyzing EV drivers’ travel decisions, considering the influence of charging and V2G pile locations and sizes. Subsequently, we tackle the Traffic Assignment Problem with User Equilibrium (TAP-UE) model to characterize the steady-state traffic flow distribution of EVs. Following this, we formulate the optimization model for the Coordinated Power and Transportation Network (CPTN), which encompasses the optimal expansion of DN facilities and traffic flow regulation under UE conditions. To mitigate the computational complexity associated with the V2G planning model, we introduce a series of linearization methods to obtain a manageable Mixed-Integer Linear Programming (MILP) solution. Finally, to validate the efficacy of our proposed planning framework, we apply it to two test systems, including a real-world case study. Through these case studies, we explore the necessity and potential benefits of V2G technologies.

A Survivor-Centered Framework for Domestic Violence Brief Crisis Intervention: A Stakeholder-Informed Approach

Program evaluation and assessment are critical for understanding the impact of domestic violence services and interventions and for making necessary refinements and revisions to programs. Demonstrating the impact of domestic violence programs (e.g., hotlines and shelters) poses challenges due to the complexities associated with abuse experiences. The use of an assessment framework will help categorize users’ multiple needs, clarify specific components of intervention approaches, and ensure that services meet clients’ needs. This article provides a comprehensive overview of a theoretical and stakeholder-informed approach used to develop an assessment framework for the National Domestic Violence Hotline (The Hotline). The research resulted in a framework which underscores the importance of survivor empowerment and support as key survivor outcomes. This article presents detailed information about the SAF-T project including methods and processes used to develop the survivor-centered framework and provides guidance for those interested in developing similar theoretical and stakeholder-informed frameworks for program planning, measuring performance, and evaluation efforts.