Mineral calcination worldwide accounts for some 5⁻10% of all anthropogenic carbon dioxide (CO₂) emissions per year. Roughly half of the CO₂ released results from burning fossil fuels for heat generation, while the other half is a product of the calcination reaction itself. Traditionally, the fuel combustion process and the calcination reaction take place together to enhance heat transfer. Systems have been proposed that separate fuel combustion and calcination to allow for the sequestration of pure CO₂ from the calcination reaction for later storage/use and capture of the combustion gases. This work presents a new tube-in-tube helical system for the calcination of minerals that can use different heat transfer fluids (HTFs), employed or foreseen in concentrated solar power (CSP) plants. The system is labeled ‘flameless’ since the HTF can be heated by other means than burning fossil fuels. If CSP or high-temperature nuclear reactors are used, direct CO₂ emissions can be divided in half.... [more]

Ecological mechanisms influence relationships among microbial communities, which in turn impact biogeochemistry. In particular, microbial communities are assembled by deterministic (e.g., selection) and stochastic (e.g., dispersal) processes, and the relative balance of these two process types is hypothesized to alter the influence of microbial communities over biogeochemical function. We used an ecological simulation model to evaluate this hypothesis, defining biogeochemical function generically to represent any biogeochemical reaction of interest. We assembled receiving communities under different levels of dispersal from a source community that was assembled purely by selection. The dispersal scenarios ranged from no dispersal (i.e., selection-only) to dispersal rates high enough to overwhelm selection (i.e., homogenizing dispersal). We used an aggregate measure of community fitness to infer a given community’s biogeochemical function relative to other communities. We also used ecol... [more]

Big Data may introduce new opportunities, and for this reason it has become a mantra among most industries. This paper focuses on examining how to develop cost and sustainable reporting by utilizing Big Data that covers economic values, production volumes, and emission information. We assume strongly that this use supports cleaner production, while at the same time offers more information for revenue and profitability development. We argue that Big Data brings company-wide business benefits if data queries and interfaces are built to be interactive, intuitive, and user-friendly. The amount of information related to operations, costs, emissions, and the supply chain would increase enormously if Big Data was used in various manufacturing industries. It is essential to expose the relevant correlations between different attributes and data fields. Proper algorithm design and programming are key to making the most of Big Data. This paper introduces ideas on how to refine raw data into valua... [more]

The bottleneck in creating dynamic models of biological networks and processes often lies in estimating unknown kinetic model parameters from experimental data. In this regard, experimental conditions have a strong influence on parameter identifiability and should therefore be optimized to give the maximum information for parameter estimation. Existing model-based design of experiment (MBDOE) methods commonly rely on the Fisher information matrix (FIM) for defining a metric of data informativeness. When the model behavior is highly nonlinear, FIM-based criteria may lead to suboptimal designs, as the FIM only accounts for the linear variation in the model outputs with respect to the parameters. In this work, we developed a multi-objective optimization (MOO) MBDOE, for which the model nonlinearity was taken into consideration through the use of curvature. The proposed MOO MBDOE involved maximizing data informativeness using a FIM-based metric and at the same time minimizing the model cur... [more]

Carbon dioxide conversion and utilization is gaining significant attention worldwide, not only because carbon dioxide has an impact on global climate change, but also because it provides a source for potential fuels and chemicals. Methanol is an important fuel that can be obtained by the hydrogenation of carbon dioxide. In this research, the modeling of a reactor to produce methanol using carbon dioxide and hydrogen is carried out by way of an ANOVA and a central composite design. Reaction temperature, reaction pressure, H₂/CO₂ ratio, and recycling are the chosen factors, while the methanol production and the reactor volume are the studied responses. Results show that the interaction AC is common between the two responses and allows improvement of the productivity in reducing the volume. A mathematical model for methanol production and reactor volume is obtained with significant factors. A central composite design is used to optimize the process. Results show that a higher productivity... [more]

A model predictive control (MPC) framework, exploiting both feedforward and feedback control loops, is employed to minimize large disturbances that occur in military water networks. Military installations’ need for resilient and efficient water supplies is often challenged by large disturbances like fires, terrorist activity, troop training rotations, and large scale leaks. This work applies the effectiveness of MPC to provide predictive capability and compensate for vast geographical differences and varying phenomena time scales using computational software and actual system dimensions and parameters. The results show that large disturbances are rapidly minimized while maintaining chlorine concentration within legal limits at the point of demand and overall water usage is minimized. The control framework also ensures pumping is minimized during peak electricity hours, so costs are kept lower than simple proportional control. Thecontrol structure implemented in this work is able to sup... [more]

Enormous advances in genetics and metabolic engineering have made it possible, in principle, to create new plants and crops with improved yield through targeted molecular alterations. However, while the potential is beyond doubt, the actual implementation of envisioned new strains is often difficult, due to the diverse and complex nature of plants. Indeed, the intrinsic complexity of plants makes intuitive predictions difficult and often unreliable. The hope for overcoming this challenge is that methods of data mining and computational systems biology may become powerful enough that they could serve as beneficial tools for guiding future experimentation. In the first part of this article, we review the complexities of plants, as well as some of the mathematical and computational methods that have been used in the recent past to deepen our understanding of crops and their potential yield improvements. In the second part, we present a specific case study that indicates how robust models... [more]

The primary objective of this work was to investigate the thermal and rheological properties of crude tall oil (CTO), a low-cost by-product from the Kraft pulping process, as a potential feedstock for biodiesel production. Adequate knowledge of CTO properties is a prerequisite for the optimal design of a cost-effective biodiesel process and related processing equipment. The study revealed the correlation between the physicochemical properties, thermal, and rheological behavior of CTO. It was established that the trans/esterification temperature for CTO was greater than the temperature at which viscosity of CTO entered a steady-state. This information is useful in the selection of appropriate agitation conditions for optimal biodiesel production from CTO. The point of interception of storage modulus (G′) and loss modulus (G′′) determined the glass transition temperature (40 °C) of CTO that strongly correlated with its melting point (35.3 °C). The flow pattern of CTO was modeled as a non... [more]

This article describes the development of a reaction database with the objective to collect data for multiphase reactions involved in small molecule pharmaceutical processes with a search engine to retrieve necessary data in investigations of reaction-separation schemes, such as the role of organic solvents in reaction performance improvement. The focus of this reaction database is to provide a data rich environment with process information available to assist during the early stage synthesis of pharmaceutical products. The database is structured in terms of reaction classification of reaction types; compounds participating in the reaction; use of organic solvents and their function; information for single step and multistep reactions; target products; reaction conditions and reaction data. Information for reactor scale-up together with information for the separation and other relevant information for each reaction and reference are also available in the database. Additionally, the ret... [more]

In recent years gas⁻liquid flow in microchannels has drawn much attention in the research fields of analytics and applications, such as in oxidations or hydrogenations. Since surface forces are increasingly important on the small scale, bubble coalescence is detrimental and leads to Taylor bubble flow in microchannels with low surface-to-volume ratio. To overcome this limitation, we have investigated the gas⁻liquid flow through micronozzles and, specifically, the bubble breakup behind the nozzle. Two different regimes of bubble breakup are identified, laminar and turbulent. Turbulent bubble breakup is characterized by small daughter bubbles and narrow daughter bubble size distribution. Thus, high interfacial area is generated for increased mass and heat transfer. However, turbulent breakup mechanism is observed at high flow rates and increased pressure drops; hence, large energy input into the system is essential. In this work Design of Experiment assisted evaluation of turbulent bubbl... [more]

Data reconciliation is a model-based technique that reduces measurement errors by making use of redundancies in process data. It is largely applied in modern process industries, being commercially available in software tools. Based on industrial applications reported in the literature, we have identified and tested different configuration settings providing a numerical assessment on the performance of several important aspects involved in the solution of nonlinear steady-state data reconciliation that are generally overlooked. The discussed items are comprised of problem formulation, regarding the presence of estimated parameters in the objective function; solution approach when applying nonlinear programming solvers; methods for estimating objective function gradients; initial guess; and optimization algorithm. The study is based on simulations of a rigorous and validated model of a real offshore oil production system. The assessment includes evaluations of solution robustness, constr... [more]

This paper is about the incremental computation of control sequences for discrete event systems in uncertain environments where uncontrollable events may occur. Timed Petri nets are used for this purpose. The aim is to drive the marking of the net from an initial value to a reference one, in minimal or near-minimal time, by avoiding forbidden markings, deadlocks, and dead branches. The approach is similar to model predictive control with a finite set of control actions. At each step only a small area of the reachability graph is explored: this leads to a reasonable computational complexity. The robustness of the resulting trajectory is also evaluated according to a risk probability. A sufficient condition is provided to compute robust trajectories. The proposed results are applicable to a large class of discrete event systems, in particular in the domains of flexible manufacturing. However, they are also applicable to other domains as communication, computer science, transportation, an... [more]

The radical copolymerization kinetics of acrylamide (AM) and the water-soluble monomer sodium 4-hydroxy-4-methyl-2-methylene butanoate (SHMeMB), formed by saponification of the bio-sourced monomer γ-methyl-α-methylene-γ-butyrolactone (MeMBL), are investigated to explain the previously reported slow rates of reaction during synthesis of superabsorbent hydrogels. Limiting conversions were observed to decrease with increased temperature during SHMeMB homopolymerization, suggesting that polymerization rate is limited by depropagation. Comonomer composition drift also increased with temperature, with more AM incorporated into the copolymer due to SHMeMB depropagation. Using previous estimates for the SHMeMB propagation rate coefficient, the conversion profiles were used to estimate rate coefficients for depropagation and termination (kt). The estimate for kt,SHMeMB was found to be of the same order of magnitude as that recently reported for sodium methacrylate, with the averaged copolymeriz... [more]

With our growing understanding of the impact of microbial communities, understanding how such communities function has become a priority. The influence of microbial communities is widespread. Human-associated microbiota impacts health, environmental microbes determine ecosystem sustainability, and microbe-driven industrial processes are expanding. This broad range of applications has led to a wide range of approaches to analyze and describe microbial communities. In particular, theoretical work based on mathematical modeling has been a steady source of inspiration for explaining and predicting microbial community processes. Here, we survey some of the modeling approaches used in different contexts. We promote classifying different approaches using a unified platform, and encourage cataloging the findings in a database. We believe that the synergy emerging from a coherent collection facilitates a better understanding of important processes that determine microbial community functions. W... [more]

The partition coefficients, Kmim, of N-methylimidazole (mim) in two-component systems composed of ionic liquid (IL) and a series of organic solvents immiscible with ILs (butyl acetate, ethyl acetate, tert-butyl methyl ether, diethyl ether and cyclohexane) were determined by a shake-flask method. The influence of different factors such as temperature, solvent polarity, mim concentration, and water content on Kmim by using 1-butyl-3-methylimidazolium chloride {[C₄C₁im]Cl} as a model compound was comprehensively studied. The calculated thermodynamic functions of transfer (∆trG⁰, ∆trH⁰, ∆trS⁰) showed that the mim migration (IL→organic phase) is a thermodynamically unfavorable and enthalpy-determined process in the temperature range of 298.15 to 328.15K; however, the results suggested that mim partition toward the organic phase can be enhanced by the rational manipulation of the extraction conditions. Experiments conducted with other 1-alkyl-3-methylimidazolim chlorides (CnC₁im]Cl (n = 6, 8... [more]

A phenomenological model was developed to describe the dynamic evolution of the batch suspension polymerization of methyl methacrylate in terms of reactor temperature, pressure, concentrations and molecular properties of the final polymer. Then, the phenomenological model was used as a process constraint in dynamic data reconciliation procedures, which allowed for the successful monitoring of reaction variables in real-time and on-line. The obtained results indicate that heat transfer coefficients change significantly during the reaction time and from batch to batch, exerting a tremendous impact on the process operation. Obtained results also indicate that it can be difficult to attain thermodynamic equilibrium conditions in this system, because of the continuous condensation of evaporated monomer and the large mass transfer resistance offered by the viscous suspended droplets.

IL-6 signaling plays an important role in inflammatory processes in the body. While a number of models for IL-6 signaling are available, the parameters associated with these models vary from case to case as they are non-trivial to determine. In this study, optimal experimental design is utilized to reduce the parameter uncertainty of an IL-6 signaling model consisting of ordinary differential equations, thereby increasing the accuracy of the estimated parameter values and, potentially, the model itself. The D-optimality criterion, operating on the Fisher information matrix and, separately, on a sensitivity matrix computed from the Morris method, was used as the objective function for the optimal experimental design problem. Optimal input functions for model parameter estimation were identified by solving the optimal experimental design problem, and the resulting input functions were shown to significantly decrease parameter uncertainty in simulated experiments. Interestingly, the deter... [more]

Water-soluble metallocene and organotin-containing polyethers were synthesized employing interfacial polycondensation. The reaction involved various chain lengths of poly(ethylene glycol), and produced water-soluble polymers in decent yield. Commercially available reactants were used to allow for easy scale up. The polymers exhibited a decent ability to inhibit a range of cancer cell lines, including two pancreatic cancer cell lines. This approach should allow the synthesis of a wide variety of other water-soluble polymers.

Recovering valuable compounds from waste streams of bio-based production processes is in line with the circular economy paradigm, and is achievable by implementing “simple-to-use” and well-established process separation technologies. Such solutions are acceptable from industrial, economic and environmental points of view, implying relatively easy future implementation on pilot- and full-scale levels in the bio-based industry. Reviewing such technologies is therefore the focus here. Considerations about technology readiness level (TRL) and Net Present Value (NPV) are included in the review, since TRL and NPV contribute significantly to the techno-economic evaluation of future and promising process solutions. Based on the present review, a qualitative guideline for resource recovery from bio-based production processes is proposed. Finally, future approaches and perspectives toward identification and implementation of suitable resource recovery units for bio-based production processes are... [more]

Energy optimization in buildings by controlling the Heating Ventilation and Air Conditioning (HVAC) system is being researched extensively. In this paper, a model-free actor-critic Reinforcement Learning (RL) controller is designed using a variant of artificial recurrent neural networks called Long-Short-Term Memory (LSTM) networks. Optimization of thermal comfort alongside energy consumption is the goal in tuning this RL controller. The test platform, our office space, is designed using SketchUp. Using OpenStudio, the HVAC system is installed in the office. The control schemes (ideal thermal comfort, a traditional control and the RL control) are implemented in MATLAB. Using the Building Control Virtual Test Bed (BCVTB), the control of the thermostat schedule during each sample time is implemented for the office in EnergyPlus alongside local weather data. Results from training and validation indicate that the RL controller improves thermal comfort by an average of 15% and energy effici... [more]

Alzheimer’s disease (AD) is a major public health threat; however, despite decades of research, the disease mechanisms are not completely understood, and there is a significant dearth of predictive biomarkers. The availability of systems biology approaches has opened new avenues for understanding disease mechanisms at a pathway level. However, to the best of our knowledge, no prior study has characterized the nature of pathway crosstalks in AD, or examined their utility as biomarkers for diagnosis or prognosis. In this paper, we build the first computational crosstalk model of AD incorporating genetics, antecedent knowledge, and biomarkers from a national study to create a generic pathway crosstalk reference map and to characterize the nature of genetic and protein pathway crosstalks in mild cognitive impairment (MCI) subjects. We perform initial studies of the utility of incorporating these crosstalks as biomarkers for assessing the risk of MCI progression to AD dementia. Our analysis... [more]

Over the years, there has been a consistent increase in the amount of data collected by systems and processes in many different industries and fields. Simultaneously, there is a growing push towards revealing and exploiting of the information contained therein. The chemical processes industry is one such field, with high volume and high-dimensional time series data. In this paper, we present a unified overview of the application of recently-developed data visualization concepts to fault detection in the chemical industry. We consider three common types of processes and compare visualization-based fault detection performance to methods used currently.

Plasticizers are commonly added to poly(vinyl chloride) (PVC) and other brittle polymers to improve their flexibility and processing properties. Phthalate plasticizers such as di(2-ethylhexyl phthalate) (DEHP) are the most common PVC plasticizers and have recently been linked to a wide range of developmental and reproductive toxicities in mammals. Our group has developed several replacement compounds that have good biodegradation kinetics, low toxicity profiles, and comparable plasticizer properties to DEHP. Knowledge of the rheology of PVC⁻plasticizer blends at elevated temperatures is crucial for understanding and predicting the behavior of the compounds during processing. In this work, the time⁻temperature profiles of PVC blended with our replacement green plasticizers—succinates, maleates, and dibenzoates, of varying alkyl chain length—are compared to blends prepared with DEHP and a commercially available non-phthalate plasticizer, di(isononyl cyclohexane-1,2-dicarboxylate) (Hexamo... [more]

The effectiveness of model-based multivariable controllers depends on the quality of the model used. In addition to satisfying standard accuracy requirements for model structure and parameter estimates, a model to be used in a controller must also satisfy control-relevant requirements, such as integral controllability. Design of experiments (DOE), which produce data from which control-relevant models can be accurately estimated, may differ from standard DOE. The purpose of this paper is to emphasize this basic principle and to summarize some fundamental results obtained in recent years for DOE in two important cases: Accurate estimation of the order of a multivariable model and efficient identification of a model that satisfies integral controllability; both important for the design of robust model-based controllers. For both cases, we provide an overview of recent results that can be easily incorporated by the final user in related DOE. Computer simulations illustrate outcomes to be a... [more]

Aerobic granular sequencing batch reactors (SBRs) are usually inoculated with activated sludge which implies sometimes long start-up periods and high solids concentrations in the effluent due to the initial wash-out of the inoculum. In this work, the use of aerobic mature granules as inoculum in order to improve the start-up period was tested, but no clear differences were observed compared to a reactor inoculated with activated sludge. The effect of the aeration rate on both physical properties of granules and reactor performance was also studied in a stable aerobic granular SBR. The increase of the aeration flow rate caused the decrease of the average diameter of the granules. This fact enhanced the COD and ammonia consumption rates due to the increase of the DO level and the aerobic fraction of the biomass. However, it provoked a loss of the nitrogen removal efficiency due to the worsening of the denitrification capacity as a consequence of a higher aerobic fraction.