Data driven infrastructure strategies in coal preparation

During the conceptual design process of fusion reactors it is useful to rapidly prototype different design concepts and assess their suitability against a range of high level requirements. Rapid prototyping allows the 'fail early' mantra of other fields to be applied to engineering design. Furthermore, the rapid generation of low fidelity analysis allows fast exploration of design space, which enables better decisions to be made during concept selection and the detailed design phase. The Paramak is an open-source tool that aims to provide automated parameter driven 3D CAD models for fusion reactor components and magnetic fusion reactors. The geometry produced is compatible with several analysis workflows and this allows iterative automated model building and analysis to help steer the design concept optimisation process. The Paramak uses CadQuery 2 to create the 3D CAD model. The Paramak framework is used to create a few example reactor configurations including: a spherical reactor, a regular large radius tokamak and a compact submersion tank reactor. Input parameters for the various reactors that the Paramak can generate generally fall into three categories: continuous ranges such as blanket thickness, integer ranges such as number of toroidal field coils and categorical parameters such as type of divertor. The Paramak facilitates parameter studies where users can investigate the impact of input design parameters on the reactor performance. The use of modern software practices allows the geometry to be continuously tested in analysis workflows to ensure it is fit for purpose. The generation of output metrics from input parameters lends itself to the use of data science and machine learning approaches in order to steer the design. The Paramak provides rapid construction of analysis ready CAD in a manner that allows the designer to save time when exploring the design space for design studies and facilitate automated generative design.

Despite a sizable corpus of pottery provenance studies in southern Africa, there has been no systematic research aimed at comparing modern and ancient production strategies. In this paper we present a model of Zulu clay acquisition and processing strategies and outline its implications for understanding the mineralogical composition of ceramics produced by early farming communities in the Thukela River basin in South Africa. Through a comparison of the mineralogical properties of modern and archaeological ceramics from the basin, we propose that clay‐processing strategies were considerably different during the first millennium A.D., while clay acquisition strategies have not changed considerably in the basin over time. © 2011 Wiley Periodicals, Inc.

Developing optimal energy management of integrated energy systems in the hybrid electricity and gas networks

This paper examines how the presence of environmental, social and governance (ESG) regulations in a country can enhance its attractiveness for foreign direct investment (FDI). I use country-level data on ESG regulations from the United Nations (UN)-supported network of investors called Principles forResponsible Investment (PRI).I find that the presence of ESG regulations in a country is significant correlated with higher FDI in high-income countries, and it is also correlated with higher FDI in emerging markets and developing economies (EMDE) when government's policies are perceived as effective.The presence of ESG regulations is instead negatively correlated with FDI attraction in an EMDE when the quality of the regulatory environment for private business development is perceived negatively.Existing literature does not draw a firm conclusion on whether ESG regulations incentivize or deter private investments; for example, the pollution-heaven hypothesis posits that private investments are drawn where there are fewer or less stringent environmental regulations.This paper contributes to the literature on the role of ESG regulations and to that on the role of policies in FDI attraction, by providing a different perspective on a country's FDI attraction potential related to the presence of country-level ESG regulations, offering a new range of opportunities for policy makers when considering the impact of ESG regulations in conjunction with the general quality and effectiveness of their regulatory system.

The modern paradigm of economic development is undergoing a fundamental transformation, expressed in the transition from the model of maximizing shareholder value to the concept of stakeholder capitalism, in which environmental, social and managerial factors (ESG) begin to play a key role. Given the high volatility of financial markets, the tightening of the climate agenda and structural changes in the Russian economy, sustainable development tools are no longer an element of the corporate image and are being transformed into real financial levers that determine companies' access to capital and their long-term sustainability. This issue is particularly relevant for enterprises in the transport industry, which is the infrastructural basis of the national economy and is characterized by high capital intensity and social significance. The purpose of the study is to theoretically substantiate and practically analyze the impact of ESG instruments on the financial condition of large transport corporations, as well as to identify mechanisms for the transformation of non-financial factors into sources of economic benefits. Based on this goal, the main objectives of the work are: classification of sustainable development instruments, assessment of their impact on operational efficiency and cost of capital, as well as identification of risks and constraints in the implementation of ESG strategies in modern macroeconomic conditions. As part of the study, the authors assessed changes in the financial performance of transport corporations through the prism of implementing the principles of sustainable development. The empirical base consists of data from the financial and non-financial statements of JSC Russian Railways and JSC Federal Passenger Company for the period 2017-2025, as well as materials from rating agencies (Expert RA, ACRA) and regulatory documents regulating the criteria for "green" projects in the Russian Federation. Methodological tools include systematic and comparative analysis, methods of horizontal and vertical analysis of reporting, the coefficient method and the assessment of specific performance indicators. According to the results of the study, it was found that the integration of ESG tools ensures the formation of four key channels of influence on the financial condition of transport corporations. It was revealed that the use of verified "green" bonds reduces the cost of borrowing by 0.15–0.3% due to the "green discount" and provides access to capital even during periods of high key interest rates. It is proved that the ecological modernization of traction train leads to a reduction in the specific consumption of fuel and energy resources by 1.8-2.1%, which is converted into savings in operating costs. It has been demonstrated that investments in human capital reduce staff turnover by minimizing transaction costs. It is recorded that the implementation of the ESG strategy, despite the temporary pressure on net profit, contributes to an increase in the total value of assets. Thus, the hypothesis of an investment lag is confirmed: short-term costs for sustainable development are offset by long-term growth in operational efficiency and market value of the business, which makes it possible to qualify ESG tools as an effective mechanism for risk management and financial optimization in conditions of macroeconomic instability.

The amount of information available for field development planning is limited, forcing the Production Strategy to be designed under great amounts of uncertainty. During its implementation, new information allows the adaptation of the strategy for economic gain. This work reproduces the field development process under geological uncertainty in case study UNISIM-I-D (benchmark case based on Namorado Field in Brazil). The main objectives are to evaluate the process and observe the evolution of risk curves, all in a controlled environment with real field features. The methodology generates new geostatistical images based on new well logs, assimilates production data using an ensemble-based method and re-optimizes the production strategy using a hybrid algorithm. The field development is carried out by repeatedly applying this framework under human supervision. Each step is customized using algorithms to simplify the implementation and to reduce computational effort, making this methodology more appealing for practical use. New data are collected from a high-resolution reference model that does not belong to the ensemble of models. The process starts with a production strategy, previously optimized under the uncertainties of the case study, which yields the real economic outcome within the original uncertain range. Results show high quality history matching that excessively reduced the risk range and the variability of the updated model sets. Optimizations on the production strategy, based on the updated ensembles, consistently increased the expected monetary value of the project without guaranteeing an increment in the real NPV. Applying the methodology repeatedly throughout the field development increased the EMV by 29% (from 1.532 to 1.975 billion USD) while the real NPV decreased 2% (from 1.346 to 1.319 billion USD), falling out of the expected range and revealing that the model sets did not fully represent the real field. The lack of good representation is aggravated by heterogeneities inherent to the unknown reservoir, which are difficult to identify using only well logs and production data. The results from the application of a closed-loop reservoir development process in a controlled environment warn against similar hidden mechanisms happening on a real field development under similar circumstances. They reveal intrinsic pitfalls in reservoir modeling that may contribute to production forecast problems and call for a reflection on how reservoir uncertainty assessment is performed. We prove that large sets of models do not guarantee coverage of geologic uncertainties as the field development process naturally changes the risk curves.

Optimizing energy hub systems: A comprehensive analysis of integration, efficiency, and sustainability

Many agricultural programmes have been formulated and implemented aimed at improving the socio-economic status of the rural farmers through adoption of improved technology regarding production, processing and marketing strategies. Root and Tuber Expansion Programme(RTEP), one of such programmes became loan effective on 31 July 2001. The study is aimed at comparing the socio-economic status of the Programme Participant Farmers and Non-programme Participant Farmers before and after RTEP. The sample size of 204 rural farmers made up of 102 PPFs and 102 NPPFs were the respondents, Proportionate random sampling and purposive sampling technique were used in selecting 102 PPFs and 102 NPPFs respectively. Data were collected with a set of validated questionnaire administered to the respondents 204 rural farmers. Descriptive statistics (mean, grand mean, standard deviation and frequency distribution) and inferential statistics (t-test and Omega squared) were used in the analysis of data. It was found that there are significant differences in the socio-economic variables compared between PPFs and NPPFs and even among PPFs after RTEP. However, the impact was not adequate, therefore RTEP should be enriched to be attractive to involve greater number of rural farmers so as to achieve greater number of rural farmers so as to achieve greater socioeconomic impact on the rural farmers in RTEP area of operation

BackgroundThe World Health Organization (WHO) has called for the elimination of cervical cancer. Unfortunately, the implementation of cost-effective prevention and control strategies has faced significant barriers, such as insufficient guidance on best practices for resource and operations planning. Therefore, we demonstrate the value of discrete event simulation (DES) in implementation science research and practice, particularly to support the programmatic and operational planning for sustainable and resilient delivery of healthcare interventions. Our specific example shows how DES models can inform planning for scale-up and resilient operations of a new HPV-based screen and treat program in Iquitos, an Amazonian city of Peru.MethodsUsing data from a time and motion study and cervical cancer screening registry from Iquitos, Peru, we developed a DES model to conduct virtual experimentation with “what-if” scenarios that compare different workflow and processing strategies under resource constraints and disruptions to the screening system.ResultsOur simulations show how much the screening system’s capacity can be increased at current resource levels, how much variability in service times can be tolerated, and the extent of resilience to disruptions such as curtailed resources. The simulations also identify the resources that would be required to scale up for larger target populations or increased resilience to disruptions, illustrating the key tradeoff between resilience and efficiency. Thus, our results demonstrate how DES models can inform specific resourcing decisions but can also highlight important tradeoffs and suggest general “rules” for resource and operational planning.ConclusionsMultilevel planning and implementation challenges are not unique to sustainable adoption of cervical cancer screening programs but represent common barriers to the successful scale-up of many preventative health interventions worldwide. DES represents a broadly applicable tool to address complex implementation challenges identified at the national, regional, and local levels across settings and health interventions—how to make effective and efficient operational and resourcing decisions to support program adaptation to local constraints and demands so that they are resilient to changing demands and more likely to be maintained with fidelity over time.

Techno-economic assessment of industrial food waste composting facility: Evaluating bulking agents, processing strategies, and market dynamics

At present, due to the errors of wind power, solar power and various types of load forecasting, the optimal scheduling results of the integrated energy system (IES) will be inaccurate, which will affect the economic and reliable operation of the integrated energy system. In order to solve this problem, a day-ahead and intra-day optimal scheduling model of integrated energy system considering forecasting uncertainty is proposed in this paper, which takes the minimum operation cost of the system as the target, and different processing strategies are adopted for the model. In the day-ahead time scale, according to day-ahead load forecasting, an integrated demand response (IDR) strategy is formulated to adjust the load curve, and an optimal scheduling scheme is obtained. In the intra-day time scale, the predicted value of wind power, solar power and load power are represented by fuzzy parameters to participate in the optimal scheduling of the system, and the output of units is adjusted based on the day-ahead scheduling scheme according to the day-ahead forecasting results. The simulation of specific examples shows that the integrated demand response can effectively adjust the load demand and improve the economy and reliability of the system operation. At the same time, the operation cost of the system is related to the reliability of the accurate prediction of wind power, solar power and load power. Through this model, the optimal scheduling scheme can be determined under an acceptable prediction accuracy and confidence level.

Currently Indonesia apply new gross split production sharing contracts for the oil & gas industry. Regulation of the Minister of Energy and Mineral Resources Number 8 of 2017 on Gross Split Production Sharing Contracts sets out a new economic structure for production sharing contracts (PSC) based on dividing gross production between the state and PSC Contractors, without a mechanism for the PSC Contractor to recover operating costs. For mature field, high operating cost regarding low production, high maintenance, and integrity issues are challenging for this new regulation. To optimize operating cost with robust and prudent planning is one of the key of success in this era. Pertamina Hulu Energi Offshore North West Java (PHE ONWJ) has started gross split scheme since January 2017 which start a new era of production sharing contracts. With the start of gross split scheme, prioritization of production is the main objective, to gain maximum productivity in terms of operating and lifting cost. The methodology to optimize operating cost is by prioritizing productive remote well platform, Normally Unmanned Installation (NUI), by ranking of potential development and its production volume. The non-potential and non-productive NUI then be assessed to be shut off or run to fail. The assessment conducted using technical and economic approach to obtain optimized result. For non-potential and productive NUI, assessment to gain more production with minimum cost is conducted. Then, development could be focused on potential and productive NUI. Foxtrot, one of flow station in PHE ONWJ working area, has eight active NUIs that are FA, FK, FG, FFB, FNB, FWB, HZEA, and HZEB. By conducting ranking of potential development and its production volume, company could focus on five Foxtrot NUIs for development (FK, FG, FFB, FWB & HZEA), two NUIs for optimization (FNB & FA), and one NUI that potential to be shut-off, HZEB. This action on the non-potential and non-productive NUI shut off could yet decrease operating cost by IDR 8.8 Billion/ year, eliminate potential personal hazard, and reduce system's backpressure due to its low API crude oil. Oil and Gas Company that operates old facilities in mature field could apply this approach to maintain their production by focusing on beneficial asset yet decrease operating cost.

Managing and measuring performance become exceedingly complex as healthcare institutions evolve into integrated health systems comprised of hospitals, outpatient clinics and surgery centers, nursing homes, and home health services. Leaders of integrated health systems need to develop a methodology and system that align organizational strategies with performance measurement and management. To meet this end, multiple healthcare organizations embrace the performance-indicators reporting system known as a "balanced scorecard" or a "dashboard report." This discrete set of macrolevel indicators gives senior management a fast but comprehensive glimpse of the organization's performance in meeting its quality, operational, and financial goals. The leadership of outpatient operations for Mayo Clinic in Rochester, Minnesota built on this concept by creating a performance management and measurement system that monitors and reports how well the organization achieves its performance goals. Internal stakeholders identified metrics to measure performance in each key category. Through these metrics, the organization links Mayo Clinic's vision, primary value, core principles, and day-to-day operations by monitoring key performance indicators on a weekly, monthly, or quarterly basis.

Effects of tillage method and crop rotation on non-renewable energy use efficiency for a thin Black Chernozem in the Canadian Prairies

For 5G base stations equipped with multiple energy sources, such as energy storage systems (ESSs) and photovoltaic (PV) power generation, energy management is crucial, directly influencing the operational cost. Hence, aiming at increasing the utilization rate of PV power generation and improving the lifetime of the battery, thereby reducing the operating cost of the base station, a hierarchical energy management strategy based on the improved dung beetle optimization (IDBO) algorithm is proposed in this paper. The first control layer provides bus voltage control to each power module. In the second control layer, a dynamic balance control strategy calculates the power of the ESSs using the proportional–integral (PI) controller and distributes power based on the state of charge (SOC) and virtual resistance. The third control layer uses the IDBO algorithm to solve the DC microgrid’s optimization model in order to achieve the minimum daily operational cost goal. Simulation results demonstrate that the proposed IDBO algorithm reduces the daily cost in both scenarios by about 14.64% and 9.49% compared to the baseline method. Finally, the feasibility and effectiveness of the proposed hierarchical energy management strategy are verified through experimental results.