Processes2015, 3(4), 730; doi:10.3390/pr3040730 - published 25 September 2015 Show/Hide Abstract
Abstract: We have become aware that a review paper  recently published in Processes contained a considerable amount of identical text and a similar structure to a previously published review paper , although some novel content was presented, including new citations and a section on smart diagnosis. [...]
Processes2015, 3(3), 701-729; doi:10.3390/pr3030701 - published 21 September 2015 Show/Hide Abstract
Abstract: In recent years, model optimization in the field of computational biology has become a prominent area for development of pharmaceutical drugs. The increased amount of experimental data leads to the increase in complexity of proposed models. With increased complexity comes a necessity for computational algorithms that are able to handle the large datasets that are used to fit model parameters. In this study the ability of simultaneous, hybrid simultaneous, and sequential algorithms are tested on two models representative of computational systems biology. The first case models the cells affected by a virus in a population and serves as a benchmark model for the proposed hybrid algorithm. The second model is the ErbB model and shows the ability of the hybrid sequential and simultaneous method to solve large-scale biological models. Post-processing analysis reveals insights into the model formulation that are important for understanding the specific parameter optimization. A parameter sensitivity analysis reveals shortcomings and difficulties in the ErbB model parameter optimization due to the model formulation rather than the solver capacity. Suggested methods are model reformulation to improve input-to-output model linearity, sensitivity ranking, and choice of solver.
Processes2015, 3(3), 684-698; doi:10.3390/pr3030684 - published 11 September 2015 Show/Hide Abstract
Abstract: The significant increase in natural/shale gas production in the US is causing major changes in the chemical and petrochemical markets. These changes include the increased supply of methanol and the decreased supply of propylene. As such, there are promising opportunities for methanol-to-propylene processes in the US. This paper provides a top-level techno-economic analysis of two pathways: methanol to olefins (MTO) and methanol to propylene (MTP). Base-case scenarios are simulated using ASPEN Plus to obtain the key mass and energy balances as well as design data. For each process, two scenarios are considered for the feedstock: buying methanol versus making it from natural gas. The return on investment (ROI) is calculated for both processes under broad ranges of the prices of natural gas, methanol, and products. In addition to the techno-economic analysis, the CO2 emissions are evaluated and compared.
Processes2015, 3(3), 664-683; doi:10.3390/pr3030664 - published 9 September 2015 Show/Hide Abstract
Abstract: Conceptual design methodology for the configuration and procedural training with an operating training simulator (OTS) in a large-scale plant for commercial bio-ethanol production is described. The aim of the study is to show how the methodology provides a powerful way for finding the best configuration and training structure of the OTS before constructing and implementing the software of the OTS. The OTS principle, i.e., to use a computer-based virtual representation of the real process plant intended for efficient training of process operators, has long since been applied in aviation and process industries for more efficient and flawless operations. By using the conceptual design methodology (sometimes referred to as bio-mechatronics) a variety of OTS configurations with this capacity was generated. The systematic approach of for targeting the users’ (i.e., the plant management and process operators) needs resulted in better understanding and efficiency in training of hands-on skills in operating the plant. The training included general standard operating procedures for running the plant under normal operation conditions with different starch materials, handling of typical frequent disturbances as well as acting in situations not described in the standard operation procedures and applying trouble-shooting.
Processes2015, 3(3), 634-663; doi:10.3390/pr3030634 - published 20 August 2015 Show/Hide Abstract
Abstract: The current methodological approach for developing sustainable biofuel processes and supply chains is flawed. Life cycle principles are often retrospectively incorporated in the design phase resulting in incremental environmental improvement rather than selection of fuel pathways that minimize environmental impacts across the life cycle. Further, designing sustainable biofuel supply chains requires joint consideration of economic, environmental, and social factors that span multiple spatial and temporal scales. However, traditional life cycle assessment (LCA) ignores economic aspects and the role of ecological goods and services in supply chains, and hence is limited in its ability for guiding decision-making among alternatives—often resulting in sub-optimal solutions. Simultaneously incorporating economic and environment objectives in the design and optimization of emerging biofuel supply chains requires a radical new paradigm. This work discusses key research opportunities and challenges in the design of emerging biofuel supply chains and provides a high-level overview of the current “state of the art” in environmental sustainability assessment of biofuel production. Additionally, a bibliometric analysis of over 20,000 biofuel research articles from 2000-to-present is performed to identify active topical areas of research in the biofuel literature, quantify the relative strength of connections between various biofuels research domains, and determine any potential research gaps.