Abbasi S.,University of Illinois at Chicago |
Diwekar U.M.,Vishwamitra Research Institute
Clean Technologies and Environmental Policy | Year: 2014
There are inherent uncertainties in the biodiesel production process arising out of feedstock composition, operating and design parameters and can have significant impact on the product quality and process economics. In this paper, the uncertainties are quantified in the form of probabilistic distribution function. Stochastic modeling capability is implemented in the ASPEN process simulator to take into consideration these uncertainties and the output is evaluated to determine impact on process efficiency and quality of biodiesel. © 2013 Springer-Verlag Berlin Heidelberg.
Diwekar U.,Vishwamitra Research Institute
Clean Technologies and Environmental Policy | Year: 2015
Sustainability is a keyword commonly used by researchers and practitioners globally. However, even defining the goals of sustainability is fraught with difficulties and hence attaining it is nearly impossible. Since sustainability is a property of the entire system, engineering sustainability requires the boundaries of the system greatly expanded. The thinking of sustainability also brings in larger time scales. In this article, I present a perspective on journey toward sustainability using systems analysis approaches from various disciplines. © 2015 Springer-Verlag Berlin Heidelberg
Lee A.J.,Vishwamitra Research Institute |
Diwekar U.M.,Vishwamitra Research Institute
Applied Energy | Year: 2012
The optimal sensor placement problem involves determining the most effective locations to place a network of sensors across an array of measurable signals, in accordance with a set of specified objectives and constraints, such as cost, performance, and sensitivity to variations in uncertain environments. In advanced power systems, such as in pulverized coal and integrated gasification combined cycle power plants, the placement of sensors on-line within the power generation process can be expensive or technically infeasible due to certain harsh environments. This paper uses advanced modeling techniques to simulate the system's steady state behavior, and to capture the variability in unknown process variables using the accuracy information from a given set of online sensors. This variability and measurement error is analyzed using a technique from information theory to determine the most cost-effective network of on-line sensors by formulating a nonlinear, stochastic binary integer problem. The solution is achieved by using an efficient sampling technique, Better Optimization algorithm for Nonlinear Uncertain Systems. The key contribution of using Fisher information as a metric for observation order is that it generalizes the Gaussian assumption on representing process and measurement variability for systems governed by nonlinear dynamics. © 2012 Elsevier Ltd.
Diwekar U.,Vishwamitra Research Institute |
Shastri Y.,Vishwamitra Research Institute
Clean Technologies and Environmental Policy | Year: 2011
Traditional process design concentrates on process simulation and profitability. However, for design for environment one has to extend the simulation framework to include chemical and process synthesis steps and multiple objectives for environmental and societal impacts. This article describes the developments in process design for environmental considerations. Incorporating environmental considerations in the early stages of design like chemical synthesis and process synthesis has larger impact on the design. Therefore, number of approaches and case studies in chemical and process synthesis for environment are presented here. Defining environmental impacts is more difficult than profitability. New models for defining environmental impacts is the focus of some papers important for design for environment. Uncertainties are large in these steps and need to be included in the computational procedures. Further, multiple objectives are involved in process design increasing the complexity of problem. © 2010 Springer-Verlag.
Agency: NSF | Branch: Standard Grant | Program: | Phase: ENVIRONMENTAL SUSTAINABILITY | Award Amount: 40.79K | Year: 2015
1552107 (Diwekar). The Trans-Atlantic Research and Development Interchange on Sustainability (TARDIS) workshops are a series of meetings on scientific topics related to environmental sustainability held every other year alternating between Austria and the United States. The first workshop was held on the subject of modeling for environmental sustainability at Schloss Seggau in Leibnitz, Austria in October 2004. Subsequent workshops were held in September of 2006 at the YMCA of the Rockies on the topic of underlying scientific principles of environmental sustainability, and in October 2008 again at Schloss Seggau on energy and environmental sustainability. The TARDIS 2012 workshop was held in April 2012 at Schloss Seggau in Leibnitz, Austria on the topic of time and time-frames for environmental sustainability. The most recent TARDIS workshop was held in June of 2014 at the YMCA of the Rockies in Colorado on the topic of social, economic, policy, and regulatory incentives to promote environmental sustainability in society. The next TARDIS workshop will be again held at Schloss Seggau in Leibnitz, Austria October 19 - 21, 2016 to explore the compatibility of economic growth and environmental sustainability.
The body of participants will be balanced to include adequate representation with respect to discipline (engineering, physics, chemistry, economics, policy, etc.), institutions (academic, government, private sector) and regional and national representation, and minorities and women will be encouraged to participate. Two reports will be produced: (1) a final report summarizing the results and conclusions and the presentations given, and (2) a briefer summary focused on policy. A WIKI site has been established and is currently being populated with the relevant information on all of the TARDIS workshops.
Agency: NSF | Branch: Standard Grant | Program: | Phase: ENVIRONMENTAL SUSTAINABILITY | Award Amount: 146.26K | Year: 2016
Diwekar, Urmila M.
The food production system generates waste streams that are characterized by high concentrations of organic matter, nitrogen- and phosphorus-containing species in water. Therefore, monitoring nitrogen and phosphorous species is important for water quality requirements for agricultural as well as energy recovery from waste streams. Currently these species are monitored via stationary monitoring stations. However nitrogen and phosphorous species move via agricultural run-off to other water systems, so portable sensors are needed that can change positionsin real time. This type of dynamic sensing requires suitable algorithms that can calculate appropriate sensor locations in real time in the face of inherent uncertainties in the fate and transport of the relevant species. To develop such an algorithmic framework to solve the problem of sensor placement in real time is the objective of this research.
This research is targeted to develop a fundamental understanding of the relationships involved in sensor placement and interaction with nutrient fate and transport of relevant species, with the goal of identifying the number and spatio-temporal positions of sensors for maximum effectiveness. Given that uncertainty is inherent, the problem of sensor placement will be formulated as a dynamic stochastic programming problem, the solution of which will be the dynamic optimal sensor deployment policy for nutrient monitoring in the face of uncertainties. Dynamic sensing with portable low cost sensors is a new area for nutrient monitoring which shows promise for food-water-energy nexus. This research will provide a theoretical basis for such an endeavor. This real time sensor placement problem will allow for the study of the spatial-temporal aspect of pollution which a constant monitoring station does not provide.
Agency: NSF | Branch: Standard Grant | Program: | Phase: | Award Amount: 39.93K | Year: 2013
1261650 (Diwekar). This grant provides partial financial support for a two-and-a-half day workshop that will bring together American and European engineers and scientists on the topic of social, economic, policy, and regulatory incentives to advance sustainability in society. NSF funds will be used only for U.S.-based researchers. The workshop will be held in the U.S. in May-June of 2014. The workshop will be organized in cooperation with the U.S. EPA and the Austrian Federal Ministry of Science. Discipines represented will include engineering, economics, ecology, law, and policy. A workshop report on outcomes will be provided to NSF and also posted on the web.
Agency: NSF | Branch: Standard Grant | Program: | Phase: | Award Amount: 135.28K | Year: 2014
Vishwamitra Reserach Institute
To produce large volumes of newly discovered unconventional gas, hydraulic fracturing of wells is commonly practiced in basins where shale gas and coal bed methane are extracted. Hydraulic fracturing of wells during oil and gas (O&G) exploration consumes large volumes of fresh water and generates larger volumes of contaminated wastewater. About 15-25% of this water returns to the surface as flowback water within 30 days of hydraulic fracturing. Produced water continues to flow for the life of the well. In addition to high salinity and hardness, the water may also contain significant levels of natural occurring radioactive materials (NORM). It is very difficult to selectively remove NORM from these waters.
New and novel model adsorbents will be researched in this work. The reserachers will collaborate of the Gas Tecnology Institute (GTI)to identify a simplified list of functions expected from high performance adsorbents and to correlate that list with the adsorbents commonly found. The PI will use computer aided molecular design (CAMD) methods for developing new environmentally benign adsorbents for NORM removal. CAMD is generally the reverse use of the group contribution method (GCM) that is used to generate molecules having desirable properties. GCM has been used to predict state properties like selectivity, relative volatility, surface tension, density, viscosity, and reactivity. The PI will develop new group contribution methods for important properties of adsorbents based on thermodynamics. Preliminary results have been obtained using GCM for physical adsorption. The PI proposes to study chemical adsorption and the Langmuir isotherm. GCM will identify the groups for environmentally benign adsorbents. These groups will be uniquely designed to generate all possible molecules by exploring all possible combinations. The properties of each group and/or the interaction parameters between groups can be theoretically calculated, experimentally obtained, or statistically regressed. From this set of groups, desired molecules can be generated by group combinations. Constraints from physical and chemical properties, as well as those from regulatory restrictions, may be imposed, and hence the number of combinations can be reduced.
However, this is the first time such an approach is proposed for generation of adsorbents for NORM separation. The PI will select top 30 from the list of new adsorbents obtained by CAMD for further study. In order to identify potentially desirable chemicals various solution algorithms are used. These include heuristic numeration, knowledge-base approaches, molecular property clusters with algebraic equations and optimization-based methods. The PI will use optimization approach for this work. CAMD methods have been applied to many areas, such as extraction solvents, polymer designs, degreasing solvents, blanket wash solvents, absorption solvents, refrigerant design, distillation solvents, reaction solvents, catalysts, value added products, crystallization solvents and foaming agents.
The proposed research is of considerable fundamental and practical significance to natural gas fracking industries. Proposed investigations concern the development of novel and powerfultools for identifying novel adsorbents for NORM removal in natural gas fracking. Adsorbents are used in numerous applications apart from hydraulic fracturing. Therefore, the framework developed in this work has a broader commercial and societal impact. The team is planning to collaborate with researchers from industries and national laboratories, building upon their prior interactions on other previous programs.
Shastri Y.,Vishwamitra Research Institute |
Diwekar U.,Vishwamitra Research Institute
Industrial and Engineering Chemistry Research | Year: 2011
Integrated Gasification Combined Cycle (IGCC) system using coal gasification is an important component of future energy alternatives. Consequently, understanding the system operation and optimizing it in the presence of uncertain operating conditions is important. Moreover, since gasification is the most important component of the system, it is particularly critical to understand the impact of uncertainty in gasification operation on the IGCC system. This article presents research conducted to achieve these objectives. The work initially focuses on developing a computational fluid dynamics (CFD) model for the single-stage coal gasifier, which is a part of the IGCC system. The impact of varying coal composition on the gasifier operations is determined from the CFD simulations. The stochastic CFD simulation results are then compared with those for an approximate gasifier model developed in ASPEN Plus as a part of the IGCC model to characterize and quantify the gasifier operation uncertainty. The CAPE-OPEN compliant stochastic simulation capability is also used to perform deterministic and stochastic multiobjective optimization of the IGCC system. This is based on the Parameter Space Investigation (PSI) method of multiobjective optimization useful for nonconvex nonlinear surface. Stochastic modeling is also useful for identifying important decision variables for such surfaces using Partial Rank Correlation Coefficients (PRCC). © 2010 American Chemical Society.
Diwekar U.M.,Vishwamitra Research Institute |
Shastri Y.N.,Vishwamitra Research Institute
Computers and Chemical Engineering | Year: 2010
This paper presents a systems analysis perspective that extends the traditional process design framework to green process design, green energy and industrial ecology leading to sustainability. For green process design this involves starting the design decisions as early as chemical and material selection stages on one end, and managing and planning decisions at the other end. However, uncertainties and multiple and conflicting objectives are inherent in such a design process. Uncertainties increase further in industrial ecology. The concept of overall sustainability goes beyond industrial ecology and brings in time dependent nature of the ecosystem and multi-disciplinary decision making. Optimal control methods and theories from financial literature can be useful in handling the time dependent uncertainties in this problem. Decision making at various stages starting from green process design, green energy, to industrial ecology, and sustainability is illustrated for the mercury cycling. Power plant sector is a major source of mercury pollution. In order to circumvent the persistent, bioaccumulative effect of mercury, one has to take decisions at various levels of the cycle starting with greener power systems, industrial symbiosis through trading, and controlling the toxic methyl mercury formation in water bodies and accumulation in aquatic biota. © 2010 Elsevier Ltd.