Early Planning Stages Research Articles

Geodesign as a boundary management process: Co-creating and negotiating sustainable landscape futures. Participatory research methods for sustainability ‐ toolkit #11

Geodesign is a participatory research and planning process that manages diverse boundaries and combines place-based local knowledge and values, design and planning expertise, and geographic information science for the purpose of collaborative and well-informed spatial planning. It is particularly effective in managing boundaries between stakeholders, knowledge frameworks, and technology. Geodesign is valuable in the early stages of planning, facilitating problem characterization and citizen involvement, as well as impact assessment.

Neoliberalism and the Complexities of Conceptualizing Community School Policy for Racial Equity

Full-service community schools are increasingly adopted as educational policy nationwide to transform educational institutions into community hubs, addressing racial and social disparities and countering deficit narratives related to marginalized youth and families. As the movement toward community schooling as an educational policy gains momentum, more research is needed to understand the complex process of conceptualizing such an initiative for racial equity. Spanning from the early planning stages to 3 years into the implementation of community schooling, this paper uncovers the tensions that emerge as school and district leaderships’ interpretation of the purpose of community schooling and root cause of racial inequity unveil conflicting conceptualizations of the community school initiative: community schooling rooted in neoliberal ideals of efficiency, coordination, and service choice, on one hand, and those rooted in more transformative approach with systemic reflection and change in classrooms, schools, and other institutions on the other.

IT PROJECT MANAGEMENT FRAMEWORKS: EVALUATING BEST PRACTICES AND METHODOLOGIES FOR SUCCESSFUL IT PROJECT MANAGEMENT

This study provides a systematic review of IT project management frameworks, examining the effectiveness, adaptability, and risk management strategies of methodologies such as Agile, Waterfall, PRINCE2, Scrum, and hybrid approaches. A total of 133 peer-reviewed articles were analyzed to gain insights into how these frameworks are being applied across various industries and project environments. The findings reveal that hybrid models, which combine the structured governance of traditional methodologies like Waterfall with the iterative flexibility of Agile, are becoming increasingly popular, especially in industries requiring both regulatory compliance and adaptability to changing requirements. Agile frameworks were shown to significantly improve project delivery speed, stakeholder satisfaction, and risk mitigation through continuous iterations and feedback loops, while traditional methodologies like Waterfall remain essential in sectors with strict documentation and control requirements. The review also highlights the critical role of risk management across all frameworks, with hybrid models offering the most comprehensive approach by integrating early-stage planning with ongoing risk assessment. Despite the success of these frameworks in IT-related industries, a notable gap was identified in their application to non-IT sectors, suggesting a need for further research to explore their broader applicability. This review underscores the continued relevance of traditional, Agile, and hybrid project management frameworks, while also pointing to future opportunities for expanding their use beyond IT.

A multi-objective approach to optimizing the geometry and envelope of rural dwellings for energy demand, thermal comfort, and daylight in cold regions of China: A case study of Shandong province

Rural dwellings in China’s cold regions face significant challenges related to energy consumption, thermal comfort, and daylight, with a projected substantial increase in energy demand in the future. Scientifically optimized design during the early planning stages can significantly enhance indoor thermal and daylight conditions, effectively reducing energy consumption. This study focuses on Shandong Province to comprehensively analyze the optimization of geometry and envelope design of rural dwellings in China’s cold regions. It employs a multi-objective optimization method, integrating genetic algorithms with dynamic energy simulations, to minimize total energy demand while ensuring thermal comfort and sufficient daylight. Utilizing the Octopus plugin in Grasshopper, in conjunction with EnergyPlus, Ladybug, and Honeybee, this research optimizes and analyzes the impact of various design variables on energy consumption, thermal comfort and daylight, including room depth, window-to-wall ratio in different orientations, thermal performance of the envelope, and related glass material parameters. The results indicate that the selected variables have significant energy-saving potential. Compared to the case study building, the optimized solutions can reduce total energy demand by over 62.41%, with the highest savings rate reaching 88.75%. This study emphasizes the importance of integrated design and optimization strategies in enhancing the sustainability of rural dwellings. It proposes both cost-free and cost-included optimization schemes: the former maximizes the energy-saving, thermal comfort and daylight potential of the selected variables, while the latter is more practically feasible considering the economic constraints of rural areas. The proposed optimization schemes provide multiple reference solutions and theoretical foundations for users of rural dwellings in China’s cold regions.

Green Chemistry and Responsible Research and Innovation: Moving Beyond the 12 Principles

Green chemistry focuses on designing products and processes that minimize hazardous substances and address pollution, resource depletion, and climate change. Green chemistry products and processes could contribute to the transition to circular economy and reaching Sustainable Development Goals. However, green chemistry philosophy offers none or little guidance on social, ethical, economic, or political aspects that are inherent to complex transition processes. Such broad and future-oriented considerations are at the heart of ‘Responsible Research and Innovation’ (RRI) approach but to date the ideas of RRI and green chemistry remain largely unconnected. This study aims to shed light on how RRI and green chemistry approaches can be combined. A refined responsible roadmapping method is proposed to help researchers to go beyond the 12 principles of green chemistry and develop inter- and transdisciplinary research agendas that address technical, environmental as well as social, ethical, economic and political considerations. The method was piloted in three research projects aspiring to develop sustainable and safe chemical processes and their applications. The study demonstrates that at the early stage of research planning, the responsible roadmapping method can facilitate the integration of RRI and green chemistry practices and the development of interdisciplinary research plans, which address technical, environmental, socio-ethical, economic and political dimensions. The implications of our study for future research on roadmapping methods as well as for policy and innovation practice are discussed.

Expanding the associations between built environment characteristics and residential mobility in high-density neighborhood unit

Global trend of urbanization has led to frequent residential mobility and urban shrinkage issues. Planners and policy makers advocate for enhancing built environment quality of neighbourhood units to address these issues. Although the impact factors and degree of the influence of the built environment on residential mobility have been studied, the nonlinear effects at the neighbourhood level, and the relative importance when considered alongside other factors, remain unclear. In this study, the central area of Nanjing using mobile phone signalling data, the 5Ds framework, machine learning algorithms, and interpretable model Shapley Additive exPlanations (SHAP) are examined. The finding shows that (1) economy and neighbourhood ties are still key drivers of relocation. (2) Optimizing highly accessible road network for short-distance travel and developing low-density urban mode has become significant methods to attract relocators, interacting with other factors to influence residential mobility. (3) High-quality neighbourhood design, diverse amenities, and proximity to natural landscapes increase willingness to relocate, (4) while religion, socio-demographics, and large-scale transportation accessibility have minimal impact. The study offers four urban development recommendations to help municipal planners and policy makers create liveable cities and cohesive communities, providing essential insights for early or renewal stage urban planning stages.

Life Cycle Assessment of Per- and Polyfluoroalkyl Substances (PFAS) Remediation Technologies: A Literature Review

The remediation of environments contaminated with per- and polyfluoroalkyl substances (PFAS) has become a growing priority due to the persistent, bioaccumulative, and toxic characteristics of these compounds. To promote green and sustainable remediation practices, it is crucial to assess and minimize the environmental impacts of PFAS remediation projects through life cycle assessment (LCA) at the early stages of planning. So far, no systematic literature review has been published to assess the current state of the art or identify the challenges associated with applying LCA to PFAS remediation. This article provides a review of the recent literature on LCAs of PFAS remediation, following the ISO 14040 and 14044 standards. The results indicate that the application of LCA to PFAS remediation remains in its infancy and is highly fragmented. Significant methodological variations, including differences in system boundaries and data quality, hinder the comparability and benchmarking of LCA results across studies. To enhance the use of LCA as a decision support tool for environmental assessment, there is a pressing need for methodological harmonization and improved practices. Key areas for improvement include enhancing data quality, reducing uncertainties, and increasing the robustness of PFAS LCAs, thereby enabling more informed and sustainable decision-making in PFAS remediation efforts.

A comparative life cycle assessment of fifth-generation district heating and cooling systems

With the growing global demand for cooling, there is a critical need for sustainable solutions that efficiently provide both heating and cooling. Fifth-generation district heating and cooling (5GDHC) systems present a promising option, integrating renewable energy and enabling energy sharing. Despite their potential, the environmental performance of 5GDHC systems has not been comprehensively studied until now. This study addresses this critical gap by conducting the first comprehensive cradle-to-grave life cycle assessment of 5GDHC systems, uniquely incorporating hybrid environmental flow coefficients. This approach significantly enhances the coverage and accuracy of the analysis compared to traditional assessment methods. Using the University of Melbourne’s proposed Fishermans Bend campus as a case study, we compare different 5GDHC configurations with a state-of-the-art traditional system. Our findings reveal that 5GDHC systems can reduce total life cycle GHG emissions by up to 52%, particularly when suitable heat sources and sinks are available. This study underscores the importance of considering life cycle impacts in the early planning stages of energy systems, positioning 5GDHC as a viable solution for the energy transition.

A qualitative, theory-based exploration of facilitators and barriers for implementation of pharmacist prescribing in chronic kidney disease.

While there is an accumulation of evidence that pharmacist prescribing is safe and effective, there is a lack of research on processes of implementation into practice, particularly for patients with complex clinical conditions such as chronic kidney disease (CKD). The aim was to explore the facilitators and barriers to the implementation of pharmacist prescribing for patients with CKD in the United Kingdom (UK). Semi-structured interviews were conducted with UK Renal Pharmacy Group members who were independent prescribers. The Consolidated Framework for Implementation Research (CFIR) underpinned the interview schedule. Interviews were recorded, transcribed, and independently coded by two researchers. A thematic approach was used for analysis, with data generation continuing until saturation of themes. Ethical approval was granted. Data saturation was achieved following 14 interviews. Most interviewees were female (n = 11), all had secondary care as their main practice setting, and were highly experienced prescribers with 8 having 11 or more years of prescribing practice. Interviewees were positive regarding the development of their prescribing practice. Facilitators and barriers emerged across all 5 of the CFIR domains. Key facilitators were aspects of inner setting (e.g., organisational support and communication) while key barriers were also related to inner setting, specifically the need for adequate structural and financial resources. This theory-based study has illuminated the facilitators and barriers for the implementation of pharmacist prescribing in CKD. There is a need to consider the resources required for implementation of prescribing practice at an early stage of planning and development.

Meningkatkan Kualitas Hidup Masyarakat Melalui Pengembangan Potensi Lokal dan Pemberdayaan Komunitas di Desa Lajuk Kabupaten Pasuruan

Community Service Learning (KKN) is a community service program conducted by students of Universitas PGRI Wiranegara. This service activity was carried out in Lajuk Village, Gondang Wetan District, Pasuruan Regency. This study employed a Community-Based Participatory Research (CBPR) approach to involve the community in every stage of the program. The research results showed that the KKN program has successfully improved access to information, environmental awareness, quality of education, and strengthened social and religious bonds in Lajuk Village. Active community participation in every program activity indicates the success of the participatory approach implemented. Overall, this KKN has proven that students can be effective agents of change in village development. Collaboration between students, the community, and the village government is the key to the success of this program. The implementation of this KKN provides important recommendations for the organization of future KKN, namely the importance of involving the community from the early planning stages, selecting work programs that are relevant to the needs of the community, and ensuring the sustainability of programs after the KKN is completed.

Syntactic flexibility and lexical encoding in aging sentence production: an eye tracking study.

Successful sentence production requires lexical encoding and ordering them into a correct syntactic structure. It remains unclear how different processes involved in sentence production are affected by healthy aging. We investigated (a) if and how aging affects lexical encoding and syntactic formulation during sentence production, using auditory lexical priming and eye tracking-while-speaking paradigms and (b) if and how verbal working memory contributes to age-related changes in sentence production. Twenty older and 20 younger adults described transitive and dative action pictures following auditory lexical primes, by which the relative ease of encoding the agent or theme nouns (for transitive pictures) and the theme and goal nouns (for dative pictures) was manipulated. The effects of lexical priming on off-line syntactic production and real-time eye fixations to the primed character were measured. In offline production, older adults showed comparable priming effects to younger adults, using the syntactic structure that allows earlier mention of the primed lexical item in both transitive and dative sentences. However, older adults showed longer lexical priming effects on eye fixations to the primed character during the early stages of sentence planning. Preliminary analysis indicated that reduced verbal working memory may in part account for longer lexical encoding, particularly for older adults. These findings indicate that syntactic flexibility for formulating different grammatical structures remains largely robust with aging. However, lexical encoding processes are more susceptible to age-related changes, possibly due to changes in verbal working memory.

RBFsim – A tool for early planning stage of riverbank filtration systems

Riverbank filtration (RBF) is increasingly being considered an effective method to support the management of water supply and the management of groundwater-river water exchange. Literature, however, provides very limited methods for the initial evaluation of the RBF system. Specifically, initial evaluations need to rely on limited data, be cost-effective, and provide sufficient useful output. The paper provides the development of a tool called RBFsim, designed for the early assessment of flow hydraulics in a riverbank filtration (RBF) scheme during site selection and optimization of well operation. The developed tool allows simplified computation (based on the Analytical Element Method or AEM) of the flow field for single and multiple wells in a 2D homogeneous and isotropic aquifer with uniform flow. The tool superimposes analytical solutions for key RBF quantities such as residence time (the time required for river water to reach the well) and the proportions of water (contributed by the river and groundwater) in the well discharge. These solutions are superimposed on the developed flow field. Additionally, the tool can be used to evaluate the impact of riverbed clogging on the operation of the RBF system. The simplified computation due to AEM and limited data requirements allows the tool to be used in handheld (smartphones) or desktop devices with or without internet connection. RBFsim results are verified by comparing them with results from MODFLOW and MODPATH simulations, which are based on entirely different (finite difference) computational schemes. The obtained results from both these models match within the error margin of less than 5%. Further, the practicality and applicability of RBFsim are illustrated using synthetic and field data. While the tool provides a matching river water contribution ratio with field data, it demonstrates the best-fit residence times primarily for higher well discharge rates. These limitations are attributed to complexities observed in the field, such as a heterogeneous aquifer and nonuniform flow. Overall, the developed tool simplifies the complex computations required, particularly for assessing the feasibility and risk of RBF schemes. The developed tool’s methods and code are open-sourced (licensed under CC-BY 4.0), which promotes personalized modifications and extensions.

Independent influences of movement distance and visual distance on Fitts' law.

Fitts' Law is one among a small number of psychophysical laws. However, a fundamental variable in Fitts' Law-the movement distance, D-confounds two quantities: The physical distance the effector has to move to reach a goal, and the visually perceived distance to that goal. While these two quantities are functionally equivalent in everyday motor behavior, decoupling them might improve our understanding of the factors that shape speed-accuracy tradeoffs. Here, we leveraged the phenomenon of visuomotor gain adaptation to de-confound movement and visual distance during goal-directed reaching. We found that movement distance and visual distance can influence movement times, supporting a variant of Fitts' Law that considers both. The weighting of movement versus visual distance was modified by restricting movement range and degrading visual feedback. These results may reflect the role of sensory context in early stages of motor planning. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Development of Novel Hybrid Intelligent Predictive Models for Dilution Prediction in Underground Sub-level Mining

Tenuous dilution estimates in underground mine production scheduling continue to cause significant variations between schedule forecasts and actual production. This arises partly from the inference of dilution from predecessor stopes’ performance, disregarding that these stopes would have undergone multiple intermediate design changes between scheduling and actual mining. The resultant drill and blast-influenced dilution factors gradually lose its robustness over longer planning horizons or when applied to greenfield or brownfield expansions that do not have prior performance data. To overcome this problem, a new methodology is proposed to predict dilution in underground sub-level open stoping (SLOS) using basic geological, geotechnical and stope design attributes available in the early stage of mine planning. The method utilises principal component analysis (PCA), classification and regression tree (CART) algorithm and stepwise selection and elimination (SSE) analysis. First, SSE analysis was conducted to identify the most important independent variables to be used with the CART algorithm (i.e., the SSE-CART model) to provide a predictive model. PCA analysis was then performed, and the new principal components were used to propose a new comparative model (i.e., the PCA-CART model). Low R2 values were observed for both models, necessitating the consolidation of dilution categories to increase the models’ prediction bandwidth. The hybrid PCA-CART model outperformed the SSE-CART model with overall F1 score prediction accuracy of 72% and target dilution category prediction accuracy of over 93% against SSE-CART’s 70% and 72%, respectively. Importantly, this study revealed a 13% minimum underestimation of dilution relative to the original design stopes.

A method for fast and accurate prediction of wind turbine thrust coefficients using classical momentum theory and power curve

Abstract The planning and development of windfarms require accurate prediction of the thrust coefficient (cT ) of wind turbines, which significantly affects the downstream wake. Traditional methods, such as blade element momentum theory (BEMT), often necessitate detailed geometric information of wind turbines for cT computation, information that is not frequently available, especially in the early stages of windfarm planning. This paper aims to address this challenge by presenting a novel and efficient approach to predict cT for horizontal-axis wind turbines (HAWTs). The proposed method integrates classical momentum theory with power curve data to estimate the average axial induction factor (a), thereby enabling the calculation of cT without requiring detailed geometric information of HAWTs. The method was validated against thirty-five existing pitch-controlled HAWTs, with R2 values ranging from 0.9604 to 0.9989. This validation confirms the accuracy of the method, making it a viable alternative to traditional techniques that demand comprehensive wind turbine geometric details. The method has demonstrated both rapidity and precision in cT computation for turbine wake analysis, ensuring high levels of prediction accuracy and potentially lowering the barrier to entry for windfarm development. Unlike existing models predominantly focused on wind turbine power curves, cT modelling has largely been overlooked. This study makes a unique contribution to the field by proposing a novel method for cT prediction, thereby filling a critical gap in windfarm planning and development. However, while the study shows promising results, further research is warranted to explore its applicability in diverse windfarm scenarios and turbine configurations.

Novel multi-level optimization of district heating systems: Managing spatial scale and equipment portfolio design

The design of district heating systems often involves the consideration of the appropriate system scope, referred to as spatial scale. In order to achieve climate-neutral heating in neighborhoods, it is necessary to address spatial scale in the early planning stages. This study presents a novel optimization method aimed at sustainable dimensioning of the district heating system by optimizing the system type, scope, and equipment simultaneously. The method quantifies the spatial scale of targeted district heating system and assists in the decision between decentralized and centralized systems by using clustering algorithms and the genetic algorithm. The proposed approach was rigorously tested in a city-scale case study against centralized pipe network and standalone approaches. Our findings reveal that the proposed methodology outperforms traditional threshold methods and fixed-scope optimization through a three-group comparative study, culminating in a globally optimal solution for district heating systems.. Finally, the study offers insights into the intricate interplay between energy systems and district heating network scopes, underscoring the pivotal role of spatial scale considerations in the design of district heating systems toward climate-neutral paradigms.

Understanding stakeholder attitudes towards low-head pumped hydro storage technology

BackgroundThe share of renewable energy feeding the European grid has been growing over the years, even though the intermittency of some renewable energy sources can induce electric grid instability. Energy storage has proven to be an effective way of reducing grid instability. Various solutions for large-scale energy storage are being researched nowadays. This study focusses on the innovative low-head pumped hydro storage (LH PHS) technology, a large-scale energy storage scheme suitable for shallow seas (5 – 30 m depth). Implementation of renewable energy technologies, such as wind farms in Europe, Asia and North America, has faced public opposition which has delayed or even cancelled the implementation of renewable energy projects. Literature about public perception of projects highlights the importance of involving stakeholders from the early stages of project planning. Considering this, the present study aims to collect stakeholder opinions (via an online survey) to determine what is necessary for a smooth implementation of LH PHS in the North Sea, both from technical and policy points of view.ResultsStakeholders from commercial parties, government authorities and local groups recognized the potential of LH PHS as a means to increase the share of renewable energies within the European power grid. Economics, bureaucratic burden, and structural safety have emerged as primary aspects of concern respecting the implementation of LH PHS. The impression of the respondents is that a low-head pumped hydro station would not have negative effects on their organizations. Furthermore, most of the engineering firms participating in the study communicated that their knowledge and resources could be involved in the construction of such an energy storage facility.ConclusionAs identified stakeholder concerns such as economics and structural safety are currently being researched, effective communication of the findings of this research is paramount to keep stakeholders informed of the ongoing progress. Two-way communication between researchers and stakeholders is recommended to enhance public acceptance of future technologies. Furthermore, is it advisable to undertake an examination of the available energy policies relevant to LH PHS.

Coping with the uncertainties of make-to-order production: a new approach for determining reliable delivery times with the throughput diagram

Make-to-order companies have to deal with particular uncertainties in their offer processing. At the early stage of planning offers, it is particularly uncertain 1) which open offers will be accepted by customers and 2) what capacity these will require. Therefore, it is particularly challenging for make-to-order companies to determine and keep to binding delivery times, so that many companies have problems achieving a high delivery reliability. In this paper, we show a simple model-based procedure to determine delivery times using the throughput diagram with early available information such as the offer requests in the planning process. Simulation studies show that the procedure, especially in combination with a CONWIP order release and an EODD sequencing rule, achieves a high delivery reliability without sacrificing other logistic objectives such as utilisation. Furthermore, the procedure proves to be very robust against random deviations of the planning parameters.

Transferable multi-objective factory layout planning using simulation-based deep reinforcement learning

Factory layout planning aims at finding an optimized layout configuration under consideration of varying influences such as the material flow characteristics. Manual layout planning can be characterized as a complex decision-making process due to a large number of possible placement options. Automated planning approaches aim at reducing the manual planning effort by generating optimized layout variants in the early stages of layout planning. Recent developments have introduced deep Reinforcement Learning (RL) based planning approaches that allow to optimize a layout under consideration of a single optimization criterion. However, within layout planning, multiple partially conflicting planning objectives have to be considered. Such multiple objectives are not considered by existing RL-based approaches. This paper addresses this research gap by presenting a novel deep RL-based layout planning approach that allows consideration of multiple objectives for optimization. Furthermore, existing RL-based planning approaches only consider analytically formulated objectives such as the transportation distance. Consequently, dynamic influences in the material flow are neglected which can result in higher operational costs of the future factory. To address this issue, a discrete event simulation module is developed that allows simulating manufacturing and material flow processes simultaneously for any layout configuration generated by the RL approach. Consequently, the presented approach considers material flow simulation results for multi-objective optimization. To investigate the capabilities of RL-based factory layout planning, different RL architectures are compared based on a simplified application scenario. Throughput time, media supply, and material flow clarity are considered as optimization objectives. The best performing architecture is then applied to an exemplary application scenario and compared with the results obtained by a combined version of the genetic algorithm and tabu search, the non-dominated sorting genetic algorithm, and the optimal solution. Finally, two industrial planning scenarios, one focusing on brownfield and one on greenfield planning, are considered. The results show that the performance of RL compared to meta-heuristics depends on the considered computation time. With time the results generated by the RL approach exceed the quality of the best conventional solution by up to 11%. Finally, the potential of applying transfer learning is investigated for three different application scenarios. It is observed that RL can learn generalized patterns for factory layout planning, which allows to significantly reduce the required training time and can lead to improved solution quality. Thus, the use of pre-trained RL models shows a substantial performance potential for automated factory layout planning which cannot be achieved with conventional automated planning approaches.

Modeling the morphological response of gravel–bed rivers subject to repeated sediment bypass tunnel operations

Introduction: Sediment bypass tunnels (SBTs) are operated during floods to re-establish sediment continuity past dams with the ultimate goal of decreasing accumulation in reservoirs. Depending on the location of the intake structure and operational conditions, SBTs may release either bed load-laden or bed load-free flows in the form of sudden floods (pulses). When evaluating the impacts of SBTs, the traditional approach has been to monitor channel changes in the years following project completion. However, by the time these impacts become evident, mitigation is challenging.Methods: This research adopts a forward-thinking methodology, emphasizing the prediction of potential impacts during the project’s early planning stages. We use a one-dimensional morphodynamic model to forecast the potential morphological response of a gravel-bed river with an idealized geometry to a series of SBT operations characteristic of projects in the Swiss Alps.Results: The morphological response of the downstream reach over the medium to long term is influenced by the alternating pattern of bed load-laden and bed load-free flow releases. This pattern is instrumental in forming a transition region near the SBT outlet hydrograph boundary layer (HBL).Discussion: Within the (HBL), fluctuations in bed elevation and slope are localized, while variations in grain-size distribution persist throughout the downstream region.