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The shift from fossil to renewable fuels presents an opportunity to tailor a fuel's molecular structure and composition to the needs of advanced internal combustion engine concepts, while simultaneously aiming for economic and sustainable fuel production. We have recently proposed a method for computer-aided design of tailor-made fuels that integrates aspects of both product and production pathway design. The present paper sets out to sequentially combine that method with experimental investigation on a single cylinder research engine and model-based early-stage process evaluation to create, validate, and benchmark a rationally designed multi-component biofuel for highly boosted spark-ignition engines. To this end, the computer-aided design approach is applied to a network of possible fuel components and their production pathways. The resulting optimal four-component fuel EBCC (50 mol% ethanol, 21 mol% 2-butanone, 15 mol% cyclopentane, and 14 mol% cyclopentanone) is analyzed with regard to combustion performance and estimated fuel production cost. Variations of both the indicated mean effective pressure and the relative air/fuel ratio were performed on an engine equipped with a compression ratio of 14.7. EBCC achieves indicated efficiencies that are significantly higher than those of RON 102 gasoline fuel and comparable to those of pure 2-butanone, an extremely knock-resistant fuel identified in a previous round of model-based fuel design. Furthermore, a strong reduction in engine-out soot emissions is observed compared to RON 102 gasoline. Early-stage process evaluation shows EBCC to have lower estimated fuel production costs than 2-butanone. Production costs of pure ethanol, however, are estimated to be even lower, mainly due to lower plant investment costs and a synthesis pathway that does not require hydrogen. The paper concludes with a brief perspective on further integration of the proposed sequential approach with the goal of co-optimizing the production and combustion of renewable fuel blends. [ABSTRACT FROM AUTHOR]

Decarbonization of the power sector offers ammonia industry an opportunity to reduce its CO2 emissions through sector coupling. Extending from our previous work, we propose a power‐based process for ammonia and nitric acid production. The coupling of nitric acid production facilitates highly efficient heat integration between steam electrolysis and the rest of the process. We investigate the economic performance of the production complex through a model‐based dynamic optimization approach, considering scenarios with or without incorporation of intermittent wind power as well as deployment of battery storage. In all cases, the wind power integration proves to be economic with a peak‐to‐base load ratio of up to 2.3. The new process reduces primary energy consumption by more than 13% compared to conventional technologies. However, it is only economically competitive with help of either a low‐cost battery storage or a higher carbon price on fossil fuels. The results also confirm the importance of considering process dynamics during process design. [ABSTRACT FROM AUTHOR]

Purpose: In recent years, an increase of occupational respiratory diseases, such as asthma caused by methacrylates, has been observed in dental personnel. In this study, the exposure of dental personnel to various volatile methacrylates was investigated. Materials and Methods: The air levels of methacrylates were measured during filling treatment while bonding agents were used in 4 dental practices in Munich, Germany. Short-term air sampling (15 min) was performed using solid phase microextraction (SPME). The SPME fibers were coated with carbowax/divinyl benzene to enrich the analytes. For analysis, the analytes were thermically desorbed from the fiber and subsequently analyzed directly by gas chromatography/ mass spectrometry. Results: The methacrylates methyl methacrylate (MMA), 2-hydroxyethyl methacrylate (HEMA), ethylene glycol dimethacrylate (EGDMA), and triethylene glycol dimethacrylate (TEG-DMA) were identified in the air of dental practices. The exposure levels of the four methacrylates varied during the filling treatments. The maximum concentrations found were 0.4 mg/m3 for MMA, 45 μg/m3 for HEMA, 13 μg/m3 for EGDMA, and 45 μg/m3 for TEG-DMA. The detection of TEG-DMA correlated with the application of bonding agents during performance of dental fillings. Conclusion: Exposure levels of different methacrylates were observed at all investigated dental practices. The maximum levels of MMA measured in this study were at least 200 times lower than the toxicologically relevant maximum allowable concentrations defined in various countries. Nevertheless, the exposure levels of methacrylates should be kept as low as possible due to the allergenic potential of some methacrylates. [ABSTRACT FROM AUTHOR]

A conceptual design study for a butadiene telomerization process is presented. The impact of catalyst selection on the process economics is included into the design study by an optimization-based approach relying on shortcut models. In comparison to the established process, investment cost of the novel designed process increase only marginally, while operating costs decrease by more than 75 %. Preliminary pilot-plant experiments indicate, however, that the economically favorable reaction concept is not stable. Consequently, alternative immobilization strategies are briefly investigated to guide future research. [ABSTRACT FROM AUTHOR]

Chemicals-based energy storage is promising for integrating intermittent renewables on the utility scale. High round-trip efficiency, low cost, and considerable flexibility are desirable. To this end, an ammonia-based energy storage system is proposed. It utilizes a pressurized reversible solid-oxide fuel cell for power conversion, coupled with external ammonia synthesis and decomposition processes and a steam power cycle. A coupled refrigeration cycle is utilized to recycle nitrogen completely. Pure oxygen, produced as a side-product in electrochemical water splitting, is used to drive the fuel cell. A first-principle process model extended by detailed cost calculation is used for process optimization. In this work, the performance of a 100 MW system under time-invariant operation is studied. The system can achieve a round-trip efficiency as high as 72%. The lowest levelized cost of delivered energy is obtained at 0.24 $/kWh, which is comparable to that of pumped hydro and compressed air energy storage systems. © 2016 American Institute of Chemical Engineers AIChE J, 63: 1620-1637, 2017 [ABSTRACT FROM AUTHOR]

Shortcut methods are valuable tools for the fast evaluation of key performance indicators in the early phase of conceptual process design. For the design of absorption columns, operation at minimum solvent demand represents a thermodynamically sound indicator, which is, however, difficult to determine because an infinite number of separation stages need to be considered. Instead, the suggested shortcut model exploits the existence of the pinch point to identify operation at minimum solvent demand. Existing shortcut concepts, such as the well-known equation of Kremser (Natl Pet News, 22, 43-49, 1930), are significantly outperformed by the novel shortcut model, which can be gradually refined to any desired accuracy. Integration into a stepwise procedure results in reliable solutions. The model covers rigorous thermodynamics; no simplifications regarding phase equilibrium, heat effects, or number of components are required. The performance of the method is illustrated by several case studies with up to seven components. © 2016 American Institute of Chemical Engineers AIChE J, 63: 1213-1225, 2017 [ABSTRACT FROM AUTHOR]

Shortcut methods are valuable tools for a comprehensive evaluation of key performance indicators in the early phase of conceptual process design. For the design of extraction columns, operation at minimum solvent demand represents a thermodynamically sound indicator, which is, however, difficult to determine. The suggested shortcut model therefore exploits the existence of the pinch point to directly identify operation at minimum solvent demand. It is solved quickly and reliably by a step-by-step procedure. The final step allows a reduction of the approximation error to any desired degree of accuracy. No simplifications regarding the number of components in the mixture or its thermodynamic behavior are introduced. Hence, arbitrary mixtures can be tackled. The performance of the method is highlighted by a fully automated screening of thousands of solvents for the recovery of fermentation products acetone, 1-butanol, and ethanol from aqueous solution. © 2016 American Institute of Chemical Engineers AIChE J, 63: 1236-1245, 2017 [ABSTRACT FROM AUTHOR]

Increasing carbon dioxide accumulation in earth’s atmosphere and the depletion of fossil resources pose huge challenges for our society and, in particular, for all stakeholders in the transportation sector. The Cluster of Excellence ‘Tailor-Made Fuels from Biomass’ at RWTH Aachen University establishes innovative and sustainable processes for the conversion of whole plants into molecularly well-defined fuels exhibiting tailored properties for low-temperature combustion engine processes, enabling high efficiency and low pollutant emissions. The concept of fuel design, that is, considering fuel’s molecular structure to be a design degree of freedom, aims for the simultaneous optimisation of fuel production and combustion systems. In the present contribution, three examples of tailor-made biofuels are presented. For spark ignition engines, both 2-methylfuran and 2-butanone show increased knock resistance compared to RON95 gasoline, thus enabling a higher compression ratio and an efficiency gain of up to 20% at full-load operation. Moreover, both fuels comprise a good mixture formation superior to the one of ethanol, especially under difficult boundary conditions. For compression ignition engines, 1-octanol enables a remarkable reduction in engine-out soot emissions compared to standard diesel fuel due to the high oxygen content and lower reactivity. This advantage is achieved without sacrificing the high indicated efficiency and low NOX emissions. [ABSTRACT FROM AUTHOR]

An adjoint sensitivity method is presented for nonsmooth semiexplicit differentialalgebraic equation systems (NDAEs) of index 1. The adjoint sensitivity system is derived for a generalization of Mayer-type functionals subject to NDAE constraints. Opposed to classical Mayer-type functionals that depend on the differential and algebraic variables evaluated only at the initial and final times, the generalization depends additionally on the evaluation at multiple interior time points. The derived adjoint sensitivity method extends and builds on the method for smooth DAEs by Cao et al. [SIAM J. Sci. Comput., 24 (2003), pp. 1076-1089] and on the method for nonsmooth ODEs by Ruban [J. Comput. Systems Sci. Internat., 36 (1997), pp. 536-542]. [ABSTRACT FROM AUTHOR]

The fractionation of lignocellulose in its three main components, hemicellulose, lignin and cellulose pulp can be achieved in a biphasic system comprising water and bio-based 2-methyltetrahydrofuran (2-MeTHF) as solvents and oxalic acid as catalyst at mild temperatures (up to 140 °C). This so-called OrganoCat concept relies on selective hemicellulose depolymerization to form an aqueous stream of the corresponding carbohydrates, whereas solid cellulose pulp remains suspended and the disentangled lignin is to a large extent extracted in situ with the organic phase. In the present paper, it is demonstrated that biomass loadings of 100 g L−1 can be efficiently fractionated within 3 h whereby the mild conditions assure that no significant amounts of by-products (e.g. furans) are formed. Removing the solid pulp by filtration allows to re-use the water and organic phase without product separation in repetitive batch mode. In this way, (at least) 400 g L−1 biomass can be processed in 4 cycles, leading to greatly improved biomass-to-catalyst and biomass-to-solvent ratios. Economic analysis of the process reveals that the improved biomass loading significantly reduces capital and energy costs in the solvent recycle, indicating the importance of process integration for potential implementation. The procedure was successfully scaled-up from the screening on bench scale to 3 L reactor. The feedstock flexibility was assessed for biomasses containing moderate-to-high hemicellulose content. [ABSTRACT FROM AUTHOR]

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Copyright of Bibliothek Forschung und Praxis is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Internally, heat-integrated distillation columns (HIDiC) and vapor recompression (VRC) constitute alternative design options to provide sustainable distillation processes. However, the design is often based on heuristic rules or the experience of the designer, as no systematic methodology driven by economics has been established so far. The increased complexity of heat-integrated columns can hardly be dealt with using simulation studies but rather calls for a systematic design procedure. A new design methodology is presented here; it builds on a superstructure, mixed-integer minimization of total annualized cost of operation and rigorous thermodynamic modeling. Optimal VRC and HIDiC designs are identified for the separation of binary, multicomponent, and nonideal mixtures and benchmarked against conventional distillation column designs. A small number of intermediate heat exchangers is optimal for these HIDiC configurations, eventually reducing to a single heat exchanger similar to VRC. Therefore, VRC designs are often more cost efficient due to simpler equipment. © 2012 American Institute of Chemical Engineers AIChE J, 2012 [ABSTRACT FROM AUTHOR]

An efficient parallel algorithm for the computation of parametric sensitivities for differential-algebraic equations (DAEs) with a focus on dynamic optimization problems is presented. A speedup of about 4 can be obtained for process models of more than 13500 DAEs and 75 parameters employing 8 processor cores in parallel using a Windows based system. The algorithm obtains its efficiency by decoupling the sensitivity equations from the state equations of the DAE. Furthermore, the costly Jacobian matrices are computed separately by other processes. The computational effort for a combined state and sensitivity integration can almost be reduced to the computational effort of the pure state integration, which is the theoretical limit of the suggested approach. [ABSTRACT FROM AUTHOR]

Geometric design methods for the conceptual design of azeotropic distillation processes are fast and efficient tools for the economic screening of different process alternatives. The second article of this two-part series presents a novel optimization-based conceptual design framework for azeotropic distillation processes, which allows a rapid screening of the different process alternatives with respect to feasibility and economic incentive. The design framework is based on the economic assessment of distillation columns by the rectification body method. The feasibility limits imposed by the azeotropes are incorporated using the split feasibility test introduced in the first part of this series. The application of the framework is highlighted with several ternary and quaternary process alternatives for the production of high-purity alcohols. © 2010 American Institute of Chemical Engineers AIChE J, 2011 [ABSTRACT FROM AUTHOR]

Geometric design methods for the conceptual design of azeotropic distillation processes are fast and efficient tools for the economic screening of different process alternatives. This two-part series presents a fully automated conceptual design method for finding an optimal recycle policy for the separation of mixtures with distillation boundaries. It does not require visualization and graphical inspection of residue curve or pinch maps and is, hence, not limited to ternary mixtures. The first part introduces a fully computational geometric split feasibility test based on bifurcation analysis. This bifurcation-based feasibility test can be used as a valuable stand-alone tool for the assessment of different separation options. It is also one of the core elements of the recycle optimization discussed in the second part of this series. © 2010 American Institute of Chemical Engineers AIChE J, 2011 [ABSTRACT FROM AUTHOR]

Ionic liquids are able to dissolve polysaccharides and lignin, but there is only scarce knowledge about the dissolution of native wood. In the present paper, wood was dissolved by the ionic liquid 1-ethyl-3-methylimidazolium acetate (EMIMAc). A quantitative balance of the dissolved compounds is presented and the investigations are complemented by in situ microscopy of native wood in EMIMAc. The resulting dissolution kinetics in EMIMAc reveals distinct differences between spruce and beech. While particles of 0.1-0.5 mm of spruce dissolve slowly (up to 40% after 24 h), beech is dissolved more efficiently (75% after 24 h and 90% after 72 h). Wood chips of 10 mm length show similar dissolution kinetics and lignin yields of up to 10%. Microscopic studies reveal a disintegration of wood in EMIMAc into cells with large specific surface area, and differences in dissolution between spruce and beech were observed. These findings explain the size-independent dissolution of wood in EMIMAc and may open up new opportunities for the pretreatment of wood in ionic liquids. [ABSTRACT FROM AUTHOR]

Dynamic systems that are subject to fast disturbances, parametrised by a disturbance vector d, undergo bifurcations for some values of the disturbance d. In this work we specifically examine those bifurcations which give rise to system trajectories that leave the domain of attraction of a desired system state. We derive equations which describe the manifold of bifurcation values (that is the manifold of disturbances d which cause the system trajectory to abandon the desired domain of attraction) and the corresponding normal vectors. The system of equations can then be used to find the smallest critical disturbance in physical, biological or other systems, or to robustly optimise design parameters of an engineered system. [ABSTRACT FROM AUTHOR]

A rigorous method is presented for the systematic identification of the structure and the parameters of transport coefficient models in three-dimensional, transient convection-diffusion systems using high-resolution measurement data. The transport is represented by a convection term with known convective velocity and a diffusion term with an unknown, generally state-dependent, transport coefficient. The identification of a transport coefficient model constitutes an ill-posed, highly nonlinear inverse problem. In our previous work [Kaxalashvili et al., SIAM J. Sci. Comput., 30 (2008), pp. 3249-3269], we presented a novel incremental identification method, which decomposes this inverse problem into easier-to-handle inverse subproblems. This way, the incremental identification method not only allows for the identification of the structure and the parameters of the model, but also supports the rigorous decision making on the best-suited transport model structure. Due to the decomposition approach, the identified transport model structure and parameters are subject to errors. To cope with the error propagation inherent in the incremental method, the present work suggests a model correction procedure as a supplement to the incremental identification method of our previous work, which results in a transport model of higher precision. The correction refers to both the model structure and parameters. No a priori knowledge on the unknown transport model structure is necessary. The identification approach is numerically illustrated for a three-dimensional, transient convection-diffusion equation which has its origin in the modeling and simulation of energy transport in a laminar wavy film flow. [ABSTRACT FROM AUTHOR]

In this paper, we consider the efficient estimation of local boiling heat fluxes from transient temperature measurements in the heater close to the heater surface. For accurate prediction, heat flux estimation is formulated as a transient three-dimensional (3D) inverse heat conduction problem (IHCP). This inverse problem is ill-posed and cannot be treated straightforwardly by established numerical methods. In order to obtain a regularized stable solution, a large-scale time-dependent PDE-constrained optimization problem has to be solved and an appropriate stopping criterion for the termination of the iterative solution process has to be chosen. Since the boiling heat flux is non-uniformly distributed on the heater surface due to the strong local activity of the boiling process, the use of a fixed uniform spatial discretization is not efficient. Instead, an adaptive mesh refinement strategy can be used to obtain an appropriate discretization which significantly reduces the total computational effort. In this work, we present an automatic algorithm incorporating an adaptive mesh refinement via a heat flux-based a-posteriori error estimation technique. The suggested algorithm can cope with both spatially point-wise or highly resolved temperature observations efficiently. It is applied to real measurement data obtained from two different types of pool boiling experiments. The numerical results show that the computational effort can be reduced significantly for given estimation quality. This adaptive IHCP solution technique can be also viewed as an efficient soft sensor to deduce unmeasurable local boiling heat fluxes. [ABSTRACT FROM AUTHOR]

The article discusses the opportunities and challenges of using biorenewables as an alternative for fossil fuels. It examines the interacting systems that are used in biorenewable processing, such as in plant production, biomass pretreatment and sustainable methods. It cites the multiscale modeling, as well as the model-based synthesis as the main methodological paradigms in chemical engineering.

Boiling heat transfer is still hard to model and to predict. Among all kinds of studies on boiling processes, the estimation of the local heat fluxes at the boiling surface is fundamental. In this article, we solve a three-dimensional transient inverse heat conduction problem (IHCP) arising from a single-bubble nucleate boiling experiment to reconstruct the local boiling heat flux from a high-resolution temperature field measured at the back side of a thin heating foil. From the mathematical point of view, this problem belongs to the class of ill-posed inverse problems and cannot be solved straightforwardly by classical numerical methods. Thus, an iterative regularization strategy based on the conjugate gradient method is applied to the solution of the considered IHCP. Ring-shaped local boiling heat fluxes which undergo a significant change during a single-bubble cycle are observed. [ABSTRACT FROM AUTHOR]

One approach to solve optimal control problems by direct methods is the so-called sequential approach or single shooting. Only the control variables are discretized resulting in a nonlinear program (NLP) which can be solved with SQP or interior point methods. This paper presents a new methodology to efficiently provide the Hessian of the Lagrangian of that resulting NLP. The algorithm is based on the second-order adjoint method and introduces the novel concept of composite adjoints to reduce the computational effort of a Hessian evaluation. Though this contribution is for the sake of simplicity restricted to single shooting, the same methodology can also be easily applied to multiple shooting. [ABSTRACT FROM AUTHOR]

The article presents a methodology for developing process models for multi-phase reaction systems. The methodology, which enables the systematic decomposition of mass transfer and chemical reaction and allows the identification of multi-phase reaction systems, is based upon the Incremental Identification Method (IIM). The IIM is described, noting that it allows researchers to test the identifiability of a system using measurement data they have available. A simulated two-phase enzyme reaction system is presented to demonstrate the identification of the intrinsic reaction kinetics in a sound and numerically robust way.

In this paper, an incremental approach for the identification of a model for transport coefficients in convection-diffusion systems on the basis of high-resolution measurement data is presented. The transport is represented by a convection term with known convective velocity and by a diffusion term with an unknown, generally state-dependent transport coefficient. The identification of the transport model for this transport coefficient constitutes an ill-posed nonlinear inverse problem. We present a novel decomposition approach in which this inverse problem is split into a sequence of inverse subproblems. In the first identification step of this incremental approach a source is estimated by solving an affine-linear inverse problem by means of the conjugate gradient method. In the second identification step a nonlinear inverse problem has to be solved to reconstruct a transport coefficient. A Newton-type method using the conjugate gradient method in its inner iteration is used to solve this nonlinear inverse problem of coefficient estimation. Finally, in the third identification step a transport model structure is proposed and identified on the basis of the model-free transport coefficient reconstructed in the two previous steps. The ill-posedness of each inverse problem is examined by using artificially perturbed transient simulation data and appropriate regularization techniques. The identification methodology is illustrated for a three-dimensional convection-diffusion equation which has its origin in the modeling and simulation of energy transport in a laminar wavy film flow. [ABSTRACT FROM AUTHOR]

Information on steady-state bifurcations, most notably stability boundaries, is frequently used for the analysis and design of nonlinear systems. The bifurcation points separate regions with different dynamic behavior and thus give valuable information about nonlinear systems. They cannot, however, reflect the impact of fast disturbances on the transient behavior of nonlinear systems. The influence of fast disturbances can be addressed by bifurcation points that are defined as critical points during the transient behavior of a dynamic system in the presence of fast disturbances. Specifically, we consider two types of points—grazing points and end-points. At a grazing point the trajectory of a nonlinear system tangentially touches a hypersurface spanned by a state or output constraint. At an end-point the trajectory crosses the hypersurface at a specified final time. These critical points unfold to manifolds in the parameter space of the nonlinear system separating parts of the parameter space that admit trajectories that do not violate the constraint from those where the constraint is violated. The parametric distance between a candidate design of a nonlinear system and the critical manifold is used as a robustness measure. As the closest connection between the design and the critical manifold is along the normal direction of the critical manifold, normal vectors are used to formulate minimal-distance constraints for a nonlinear program. Thus it is possible to robustly take into account state and output constraints in the presence of fast disturbances for the design of a nonlinear system. Application of the approach to closed-loop systems allows for an integration of operating point and control design. Several case studies from chemical engineering are presented to illustrate the proposed method. [ABSTRACT FROM AUTHOR]

Toxicity potentiation of two monomers [bisphenol-A-glycidyldimethacrylate (BisGMA) and urethanedimethacrylate (UDMA)] as well as two comonomers [triethyleneglycoldimethacrylate (TEGDMA) and 2-hydroxyethylmethacrylate (HEMA)], each in combination with H2O2, was investigated on the viability on human gingival fibroblasts (HGF) and human pulpal fibroblasts (HPF). The applied concentration of H2O2 was 0.06 or 0.1 mmol/l, respectively, corresponding to the EC0 of H2O2 in HGF or HPF. The cell viability was assessed by the XTT test. From this test the half maximum effect concentrations (EC50) were calculated from fitted sigmoidale curves. EC50 values were (HGF; mmol/l; mean ± s.e.m.; n = 5): HEMA 11.9 ± 0.9, TEGDMA 3.7 ± 0.3, H2O2 0.36 ± 0.04, UDMA 0.27 ± 0.08, and BisGMA 0.11 ± 0.03. No significant ( P < 0.05) differences in the EC50 values were observed when HGF was exposed to substances, as compared to HPF. No significant decrease of the EC50 values was found when HGF or HPF, respectively, was exposed to HEMA or BisGMA in addition with H2O2 up to the concentration of 0.1 mmol/l, as compared to those EC50 values of each compound without H2O2 addition. A significant decrease of the TEGDMA EC50 value from 3.7 to 2.1 or 0.4 mmol/l, respectively, was found when cells were exposed to TEGDMA in combination with H2O2 (0.06 or 0.1 mmol/l), as compared to that TEGDMA EC50 value without H2O2 addition. A significant decrease of the UDMA EC50 value from 0.27 to 0.11 or 0.08 mmol/l, respectively, was found when HGF or HPF was exposed to UDMA in combination with H2O2 (0.06 or 0.1 mmol/l), as compared to that UDMA EC50 value without H2O2 addition. The addition of H2O2 (0.06 or 0.1 mmol/l) resulted in a toxicity potentiation of TEGDMA and UDMA, but not of HEMA and BisGMA, on HGF or HPF. [ABSTRACT FROM AUTHOR]

The article offers information on a model-based run-to-run process control approach, in which the manipulated variables are optimized after each filtration cycle. It is noted that due to the complex mechanisms involved, membrane filtration processes are mostly operated with fixed values of the manipulated variables, leaving much of the economical potential unexplored. The evaluation of the process control approach involved a case study on submerged membrane filtration in wastewater treatment. A simulation environment employing a validated reference model was used to test the resulting model-based controller. Results with respect to prediction quality and optimization results are discussed.

We propose a novel approach for the parametrically robust design of dynamic systems. The approach can be applied to system models with parameters that are uncertain in the sense that values for these parameters are not known precisely, but only within certain bounds. The novel approach is guaranteed to find an optimal steady state that is stable for each parameter combination within these bounds. Our approach combines the use of a standard solver for constrained optimization problems with the rigorous solution of nonlinear systems. The constraints for the optimization problems are based on the concept of parameter space normal vectors that measure the distance of a tentative optimum to the nearest known critical point, i.e., a point where stability may be lost. Such normal vectors are derived using methods from nonlinear dynamics. After the optimization, the rigorous solver is used to provide a guarantee that no critical points exist in the vicinity of the optimum, or to detect such points. In the latter case, the optimization is resumed, taking the newly found critical points into account. This optimize-and-verify procedure is repeated until the rigorous nonlinear solver can guarantee that the vicinity of the optimum is free from critical points and therefore the optimum is parametrically robust. In contrast to existing design methodologies, our approach can be automated and does not rely on the experience of the designing engineer. A simple model of a fermenter is used to illustrate the concepts and the order of activities arising in a typical design process. [ABSTRACT FROM AUTHOR]

Even though multicomponent mixtures are ubiquitous in mass transfer processes, mutual diffusion data in these systems are scarce. This is due to the fact that established diffusion measurements are laborious. In particular, several experiments are required to determine multicomponent diffusion coefficients at a single composition. In order to overcome these deficiencies, a diffusion experiment employing one-dimensional Raman spectroscopy is presented. Concentrations of the individual species are resolved with high spatial and temporal resolution during the diffusion process. In this work, it is shown that these data allow determining the ternary Fick diffusion matrix from a single isothermal diffusion experiment. The experimental procedure is further optimized using model-based experimental design techniques, where general design guidelines for diffusion experiments are derived. Thereby, precision of the diffusion measurements can be improved by an order of magnitude. The theoretical calculations are validated by experimental results for the system n-propanol + 1-chlorobutane + n-heptane. [ABSTRACT FROM AUTHOR]

The solution of linear inverse heat conduction problems (IHCP) for the reconstruction of time-dependent, spatially unknown heat fluxes on the boundaries of two- and three-dimensional geometries from several temperature measurements is presented. The solution method is based on the interpretation of the IHCP in the frequency domain, tie emphasize the extension of the method to large-scale problems. In particular, we consider the parameterization of the unknown heat fluxes with respect to the number of sensors and their positions and the reduction and stable inversion of the large linear state-space models obtained from semidiscretization of the heat conduction equation. The influence of each of the steps and the choice of their tuning parameters on the quality of the estimated heat flux are discussed. Two- and three-dimensional examples show the good performance of the method with regard to time and space resolution in the presence of noisy measurements. [ABSTRACT FROM AUTHOR]

Extractive distillation is a common process for the separation of homogeneous azeotropic mixtures with a minimum boiling azeotrope. In this process entrainer feed flow rate and reflux ratio of the extractive column represent the crucial design degrees of freedom that govern feasibility and operating cost. In this work feasibility and operational stability of the extractive column are related to the nonlinear analysis of the extractive section. A fully automated conceptual shortcut design method for the simultaneous determination of minimum entrainer feed flow rate and minimum reflux ratio is presented. The method is applicable to arbitrary multicomponent mixtures and allows direct screening of design alternatives and comparison of different entrainers. [ABSTRACT FROM AUTHOR]

The established technique for simulation of refinery processes is the use of pseudocomponents. However, in order to increase the economical benefit of plant operation, it seems inevitable to include molecular information in petroleum mixtures characterization. This will lead to a strong increase of problem size. For this new class of models, there currently seems to be no special algorithms available. The classic pseudocomponent approach is compared with a newly developed solution strategy, which is explicitly developed to efficiently solve simulation problems with a high detail in composition representation. The new solution strategy is an adaptive multigrid method based on a wavelet-Galerkin discretization. With the wavelet-Galerkin discretization the model can easily be formulated on various levels of detail. In an iterative procedure the multigrid concept exploits these different formulations to construct correction-term approximations to the true solution. The discretization of these correction-term models is now done with a detail in composition representation that is determined by a residual-based adaptation strategy. The proposed method has been implemented for a simple 9-stage distillation column and tested for a variety of feed mixtures. In all investigated tests the proposed method proved to be superior to the conventional pseudocomponent approach in terms of accuracy and efficiency. [ABSTRACT FROM AUTHOR]