Conceptual chemical process design in a sustainable technological world

This paper investigates energy consumption patterns using panel data of final energy consumption and economic variables from 1970 to 2010 for more than 100 countries and regions. Although previous economic studies address the role of economic development and income as determinant factors of energy consumption, we examine how physical factors such as climate affects energy consumption level and patterns. By integrating economic and engineering approaches, we demonstrate statistical analyses showing that climate determines not only energy consumption levels, but also the relationship between energy consumption and income levels over time. While climate affects energy consumption patterns, our results suggest that energy technology and price policy are significant in determining whether a country can decouple energy consumption from economic growth.

A new scheme for ammonia and fertilizer generation by coal direct chemical looping hydrogen process: Concept design, parameter optimization, and performance analysis

Performing a pollution prevention assessment of a chemical process design is typically resource intensive. Time constraints, a lack of resources and limited inhouse expertise, particularly in developing nations, have resulted in inconsistent and non-routine identification of pollution prevention opportunities. To address these problems, computer based tools may be developed to enable designers to rapidly understand environmental implications and provide suggestions of process modifications. A software prototype, P2TCP (Pollution Prevention Tool for Continuous Processes) is presented. P2TCP provides support and helps facilitate pollution prevention assessments of continuous chemical processes at all stages of design.There is a significant need for quantitative methods for comparison of process alternatives. Although chemical and safety hazard rating schemes have a long history, there is no universally accepted method for comparison in terms of potential environmental impacts. Full health and environmental risk analysis is not suitable for conceptual process design decision making but models or indicators can provide a suitable approach. A number of methods are incorporated in P2TCP.The benefits of heat and mass integration tools for pollution prevention (P2) have been widely demonstrated. However no tool has been developed specifically to assist in the intuitive process of systematically identifying alternatives for continuous chemical processes which may reduce waste generation and energy consumption. P2TCP incorporates an expert system for P2 design analysis which is complementary to existing integration and simulation tools. The key features of the analysis system are presented.KeywordsChemical process design analysisenvironmental comparisonpollution prevention

A Nonlinear Programming Approach to Conceptual Design of Reaction-Separation Systems

Computer tool supported process design methodology

This study analyzes the impact of energy security and geopolitical risks on energy consumption in countries with geopolitical risk from 1985 to 2021, with the aid of financial development, economic growth, and human capital as moderating variables. Employing robust panel data econometric techniques, the analysis reveals that heightened geopolitical risks and compromised energy security significantly affect energy consumption patterns. The increase in energy security risk by 1% has a dual impact on energy consumption patterns in countries with high geopolitical risk, as renewable energy consumption increases by 0.1227%, while non-renewable energy consumption also increases by 0.113%. As geopolitical risk increases by 1%, energy consumption patterns change, decreasing renewable and non-renewable energy consumption. Specifically, renewable energy consumption decreases by 0.00010% with a 1% rise in geopolitical risk. A 1% increase in financial development significantly impacts energy consumption in these countries. The adoption of sustainable energy solutions is positively correlated with the development of financial markets in high-risk countries, with non-renewable energy consumption decreasing by 0.0187% as financial development progresses. Additionally, an increase in economic growth of 1% leads to a 0.6750% increase in renewable energy consumption, indicating a preference for renewable sources as economies expand, aligning with global sustainability efforts. The findings underscore the importance of resilient energy policies considering geopolitical uncertainties while promoting sustainable economic development. This study offers critical insights for policymakers aiming to balance energy security with financial stability in geopolitically sensitive regions, providing a comprehensive framework to guide strategic decisions in the face of evolving global risks.

In industrial practice, conceptual process design is typically conducted by repetitive simulation studies, which require detailed design specifications in an early design phase. Guided by heuristics, these iterative solution procedures result in high manual effort and, in addition, no guarantee concerning the quality of the solution can be given. Optimization-based design methods provide a tremendous potential to accelerate and improve conceptual process design. For this purpose, a synthesis framework for the optimization-based design of chemical processes is presented in this thesis. Powerful shortcut and rigorous evaluation methods for reaction and distillation are presented. These methods are computationally efficient in order to allow an optimization-based design of large-scale chemical processes. Various industrial case studies illustrate the application of the novel approaches and highlight their benefits. ...

Excerpts reprinted with permission from Parvatker, A. G.; Eckelman, M. J. Comparative Evaluation of Chemical Life Cycle Inventory Generation Methods and Implications for Life Cycle Assessment Results. ACS Sustain. Chem. Eng. 2019, 7 (1). Copyright 2019 American Chemical Society. Excerpts reprinted with permission from Parvatker, A. G.; Tunceroglu, H.; Sherman, J. D.; Coish, P.; Anastas, P.; Zimmerman, J. B.; Eckelman, M. J. Cradle-to-Gate Greenhouse Gas Emissions for Twenty Anesthetic Active Pharmaceutical Ingredients Based on Process Scale-Up and Process Design Calculations. ACS Sustain. Chem. Eng. 2019, 7 (7), 6580-6591. Copyright 2019 American Chemical Society. Excerpts reprinted with permission from Parvatker, A. G.; Eckelman, M. J. Simulation-Based Estimates of Life Cycle Inventory Gate-to-Gate Process Energy Use for 151 Organic Chemical Syntheses. ACS Sustain. Chem. Eng. 2020, 8 (23), 8519-8536. Copyright 2019 American Chemical Society. Synthetic chemicals are ubiquitous and are an integral part of almost every value chain in the industrialized world. Hence, comprehensive assessment of health and environmental impacts over the chemicals life cycle is critical in the pursuit of sustainable development, using quantitative modeling tools such as life-cycle assessment (LCA). However, lack of primary production data, and time- or resource-intensive design calculations often forces LCA practitioners to rely on simplistic methods for estimating chemical process data. Use of such "shortcut" methods for calculating chemical life cycle inventory (LCI) data introduces uncertainties and inaccuracies in environmental sustainability analysis. Research in this doctoral dissertation focuses on developing and implementing novel methods to reduce the time and resources required in chemical LCI data generation. An analysis of eight alternative methods to account for missing chemical LCI data was conducted to identify their strengths and drawbacks. Out of the four methods with whichfull LCIs can be generated, the advanced process-based methods give the most accurate life cycle GHG emission results compared to plant data for the case studies of styrene and its downstream product, acrylonitrile-butadiene-styrene (ABS). Stoichiometric calculations, which are the most commonly used approach, underestimate the actual global warming results by 35-50%.1 Among the 18 impact categories of the ReCiPe LCIA method, results for the estimated LCI data were within 10% of the actual plant results for only 4-5 categories. These techniques were then used in conjunction with a novel process scale-up and design method to estimate LCIs and cradle-to-gate greenhouse gas emissions for twenty common active pharmaceutical ingredients (API) used as injectable anesthetics and 130 intermediate pharma compounds. The cradle-to-gate GHG emissions of the 20 anesthetic drugs range from 11 kg CO2 eq. for succinylcholine to 3,000 kg CO2 eq. for dexmedetomidine. The LCI methods and data generated in this work greatly expand the available environmental data on APIs and can serve as a guide for LCA practitioners in future analysis of other pharmaceutical drugs. Process energy is a key input in a chemical LCI and has significant impact on LCA results. A streamlined process simulation-based methodology was developed to estimate energy consumption in chemical manufacturing. The methodology is applied to 151 different chemical processes using Aspen Plus to estimate their gate-to-gate process energy use, representing the largest such simulation-based LCI data set to date.3 The results from process simulations were then used to develop predictive models for heating and cooling requirements in chemical production. The multiple linear regression (MLR) and artificial neural network (ANN) models with R2 of 0.63 to 0.73 with measured error of less than 50% are robust alternatives for rapid estimations and screening analysis compared to the current methods used in LCI databases. The series of methods presented in this work can be used with varying availability of chemical synthesis data for life cycle inventory modeling. This research not only introduces and demonstrates novel methods for chemical LCI data estimation but also adds a significant number of new LCI data sets to the literature.--Author's abstract

The COVID-19 pandemic has generated multiple impacts. In particular, in the educational sector, the virtual class modality generated changes in the patterns of energy consumption at the institutional level; the identification of this consumption will allow us to reflect on new energy saving and efficient use strategies. In this research, we present a case study of the effects of the COVID-19 pandemic on electricity consumption in 13 state universities in Michoacán, Mexico. Electric energy consumption has been evaluated before and during the presence of the COVID-19 between 2019 and 2020. The comparative analysis estimated the reduction in energy consumption and its economic and environmental impact. The results show a considerable decrease in electricity consumption, generating an average saving of 76.24 MWh/month, which translates into an annual emission reduction from 2019 to 2020 of approximately 497 TnCO2e, and in economic terms of $8,882.25 USD each month. In general, it was identified that consumption patterns in the use of machinery and computer equipment for administrative activities were drastically reduced. If education continues in virtual or hybrid modes, energy consumption schemes will continue to decline and institutions could move towards resilient, affordable, and sustainable models of energy production and consumption.

Process simulation is a critical cornerstone of chemical engineering design. Current automated chemical design methodologies focus mainly on various representations of process flow diagrams. However, transforming these diagrams into executable simulation flowsheets remains a time-consuming and labor-intensive endeavor, requiring extensive manual parameter configuration within simulation software. In this work, we propose a novel multi-agent workflow that leverages the semantic understanding capabilities of large language models(LLMs) and enables iterative interactions with chemical process simulation software, achieving end-to-end automated simulation from textual process specifications to computationally validated software configurations for design enhancement. Our approach integrates four specialized agents responsible for task understanding, topology generation, parameter configuration, and evaluation analysis, respectively, coupled with Enhanced Monte Carlo Tree Search to accurately interpret semantics and robustly generate configurations. Evaluated on Simona, a large-scale process description dataset, our method achieves a 31. 1% improvement in the simulation convergence rate compared to state-of-the-art baselines and reduces the design time by 89. 0% compared to the expert manual design. This work demonstrates the potential of AI-assisted chemical process design, which bridges the gap between conceptual design and practical implementation. Our workflow is applicable to diverse process-oriented industries, including pharmaceuticals, petrochemicals, food processing, and manufacturing, offering a generalizable solution for automated process design.

The purpose of this study is to return to Freud’s original descriptions of the primary and secondary processes in the light of modern neurosciences. In his Project for a Scientific Psychology, Freud draws the axes of the architecture of a mental apparatus: on a horizontal plane, the primary process transfers the excitation by impinging stimuli over a sequence of analogous states towards their discharge; thus, the primary process is essentially characterized by its associative tendency. On a vertical plane, the secondary process opposes the primary bottom-up pressure by a top-down inhibition with its origins in the purposive idea: the secondary process is essentially characterized by its inhibitory interventions. Freud later proposed that the primary and secondary process are seeking for perceptual, respectively thought identity. These different elements are coherent with the dynamics of the ventral and dorsal brain pathways respectively. Moreover, the dorsal pathway has an inhibitory influence upon the ventral pathway, much like the secondary has upon the primary. This influence is exerted thanks to what Freud called the “indications of reality.” We propose to equate these indications with the efference copies in modern neurosciences since they proceed from the same physiology and have the same function, besides originating from the same Helmholtzian source. Finally, even if both primary and secondary processes serve the death drive through the pleasure and the reality principle respectively, only the secondary process, requiring the bearing of an accumulation of excitations, also serves the life drive.

The importance of energy consumption and environmental protection is one of the key issues of the past decade. Most of the energy consumption during the summer season in residential buildings, offices, hospitals, and hotels is related to their chiller plant. The highly variable cooling demand of the buildings connected to a hybrid chiller plant has to be distributed among absorption and vapor compression chillers to achieve higher energy efficiencies. Cooling load sharing strategies in chiller plants have a significant impact on energy consumption and consequently with more productivity and environmentally protected. This paper examines the behavior and pattern of energy consumption in a hybrid chiller plant that includes a combination of vapor compression and absorption chillers. In order to properly understanding the pattern of energy consumption, an existing mechanical room for a hospital in Tehran has been studied for six months and its energy consumption has been compared with the software modeling. This comparison includes the capacity of each chiller, the amount of energy consumed by vapor compression chillers and absorption chillers, and the percentage of their cooling energy allocation. The results indicate that the sequence of the chiller function and how they are placed in the circuit during a partial load is in the highest importance in viewpoint of energy saving.

Integration of life cycle assessment software with tools for economic and sustainability analyses and process simulation for sustainable process design

Chemical manufacture is a significant value-added industry in both local and global economies. Along with highly relevant issues such as unsustainable process design, energy consumption, and waste generation linked with the sector, societal issues relating to chemical product health and safety are part of the greater sustainability concerns. There is a need to design a sustainable strategy while ensuring economic stability at the corporate level. Hence, this paper presents a methodological proposal of integrated modelling approach for sustainable chemical process design at early design process. The step of achieving this objective is separated into several parts. The first step is to classify parameters from established tools as a benchmark for sustainability metrics. The next step is to transform quantification value of triple bottom line impact (economic, environment and social) to normalized weightage by using Multi Criteria Analysis. The final stage is to develop alternative in terms of technical optimization of process design. The implementation multimodal Multi Criteria Analysis and optimized process design exhibits significant improvements in sustainability impacts according to the waste reduction (WAR) algorithm.

One of the priority issues in green chemistry is to devise of greener and sustainable chemical strategies and processes to reduce or eliminated the use of hazardous substances. The development of bio-based materials has been constantly increasing, and there is a global effort in agreement with the demands of sustainable management for reducing reliance of fossil resources. In this sense there are green polymerization systems improved to reach increased yields and produce polymers with high molar mass and with specific microstructure characteristics. In the same way, biocatalysis in green chemistry reactions are performer under mild conditions of temperature, pressure and pH. However, along with new materials, chemical processes and reactors must be redesign and developed to guarantee the requirements and meet the demand for green chemical products. Substantial differences with traditional chemical process are based on the synthesis of materials changing the solvents selections and the implementation of continuous reactors, as well as in evaluating the effectiveness of the process through factors such as atom economy, environmental factor, and process mass intensity to implement an industrial green process. This chapter is a review of the processes that have been design and developed to achieve to maximize efficiency and reduce waste.