Optimal curing for thermoset matrix composites: Thermochemical and consolidation considerations

A design sensitivity method is used to find optimal autoclave temperature and pressure histories for curing of thermoset-matrix composite laminates. The method uses a finite element simulation of the heat transfer, curing reaction, and consolidation in the laminate. Analytical sensitivities, based on the direct differentiation method, are used within the finite element simulation to find the design sensitivities, i.e., the derivatives of the objectives function and the constraints with respect to the design variables. Standard gradient-based optimization techniques are then used to systematically improve the design, until an optimal process design is reached. In this study the objective is to minimize the total time of the cure cycle, while the constraints include a maximum temperature in the laminate (to avoid thermal degradation) and a maximum deviation of the final fiber volume fraction from its target value (to achieve proper consolidation). The simulations of curing process are performed for EPON 862/W epoxy under a conventional cure cycle, for both thin and thick parts. Time-optimal cure cycles are found using the optimization program. Simulations of fast-curing cycles are also examined. The optimal cycles are similar in form to conventional cure cycles, but give substantially shorter cure times. The entire scheme works automatically and efficiently, simultaneously adjusting multiple design variables at each iteration.     

Comparison of Two Processes for Manufacturing Ceramic Matrix Composites from Organometallic Precursors

A commercial polysilazane is used as a silicon carbonitride matrix precursor for the manufacture of ceramic matrix composites using bi-directional SiC Nicalon fabrics as reinforcing material. The objective is to develop a simple and fast process leading to materials able to compete with SiC/C/SiC composites obtained by the Chemical Vapour Infiltration (CVI) route. Two processes are investigated: (1) a ‘conventional’ process using the densification of a SiC fibre preform by several cycles of impregnation of the preform with the polymer followed by pyrolysis and (2) a ‘modified’ process consisting in a powder filling of the fibre preform prior to the precursor impregnation and pyrolysis. This paper describes the different steps of both processes. The materials obtained are characterised in terms of their porosity, microstructure and mechanical properties. ©     

Optimal cure steps for product quality in a tire curing process

Numerical algorithms and computer programs have been developed to determine optimal cure steps in a tire curing process. A dynamic constrained optimization problem was formulated with the following ingredients: (1) an objective function that measures product quality in terms of final state of cure and temperature history at selected points in a tire; (2) constraints that consist of a process model and temperature limits imposed on cure media; (3) B‐splines representation of a time‐varying profile of cure media temperature. The optimization problem was solved using the complex algorithm along with a finite element model solver. Numerical simulations were carried out to demonstrate the procedure of determining optimal cure steps for a truck/bus radial tire. © 1999 John Wiley & Sons, Inc. J Appl Polym Sci 74: 2063–2071, 1999     

Reference Trajectory Optimization Under Constrained Predictive Control

Chemical process systems often need to respond to frequently changing product demands. This motivates the determination of optimal transitions, subject to specification and operational constraints. However, direct implementation of optimal input trajectories would, in general, result in offset in the presence of disturbances and plant/model mismatch. This paper considers reference trajectory optimization of processes controlled by constrained model predictive control (MPC). Consideration of the closed‐loop dynamics of the MPC‐controlled process in the reference trajectory optimization results in a multi‐level optimization problem. A solution strategy is applied in which the MPC quadratic programming subproblems are replaced by their Karush‐Kuhn‐Tucker optimality conditions, resulting in a single‐level mathematical program with complementarity constraints (MPCC). The performance of the method is illustrated through application to two case studies, the second of which considers economically optimal grade transitions in a polymerization process.     

Optimal operation of cryogenic air separation systems with demand uncertainty and contractual obligations

Cryogenic air separation is an efficient technology for supplying large quantities of nitrogen, argon, and oxygen to chemical, petroleum and manufacturing customers. However, numerous uncertainties make effective operation of these complex processes difficult. This work addresses the problem of determining an optimal operating strategy to maximize the total profit of a cryogenic air separation process while considering demand uncertainty and contractual obligations. A rigorous process model is included as constraints in a nonlinear programming formulation. Uncertain demands are assumed to be normally distributed with known mean and standard deviation, and expected profit in the objective function is evaluated using the standard loss function. A probabilistic fill-rate expression, also based on the loss function, is used to model the contractual obligations by providing a lower bound on the expected product sales. In the single period case with one customer satisfaction constraint, the nonlinear programming formulation can be solved efficiently using the general purpose nonlinear optimization package, Ipopt. This formulation is then extended to include multiple time periods, the potential for product storage, and customer satisfaction constraints on multiple products. To solve the large-scale nonlinear programming formulation that considers a seven-day operating horizon, a tailored parallel nonlinear programming algorithm is used. This approach makes use of a Schur complement decomposition strategy to exploit the block structure of the problem and allow efficient solution in parallel. Using these tools, we solve for a set of optimal operating strategies over the complete space of different fill rates. This produces planning figures that identify key trade-offs between profitability and contractual obligations.     

Development of an optimal multifloor layout model for the generic liquefied natural gas liquefaction process

Liquefied natural gas (LNG) is attracting significant interest as a clean energy alternative to other fossil fuels, mainly for its ease of transport and low carbon dioxide emission. As worldwide demand for LNG consumption has increased, liquefied natural gas floating, production, storage, and offloading (LNG-FPSO) operations have been studied for offshore applications. In particular, the LNG-FPSO topside process systems are located in limited areas. Therefore, the process plant layout of the LNG-FPSO topside systems will be optimized to reduce the area cost occupied by the topside equipment, and this process plant layout will be designed as a multifloor concept. We describe an optimal layout for a generic offshore LNG liquefaction process operated by the dual mixed refrigerant (DMR) cycle. To optimize the multifloor layout for the DMR liquefaction cycle process, an optimization was performed by dividing it into first and the second cycles. A mathematical model of the multifloor layout problem based on these two cycles was formulated, and an optimal multifloor layout was determined by mixed integer linear programming. The mathematical model of the first cycle consists of 725 continuous variables, 198 equality constraints, and 1,107 inequality constraints. The mathematical model of the second cycle consists of 1,291 continuous variables, 286 equality constraints, and 2,327 inequality constraints. The minimization of the total layout cost was defined as an objective function. The proposed model was applied to DMR liquefaction cycle process to determine the optimal multifloor layout.     

In situ monitoring of residual strain development during composite cure

Internal (residual) stresses build up in a thermosetting composite as the matrix shrinks during cure, and again as the composite is cooled to ambient from its elevated processing temperature. These stresses can be significant enough to distort the dimensions and shape of a cured part as well as initiate damage in off‐axis plies, either during fabrication or under the application of relatively low mechanical loads. The magnitude of these stresses depends on a number of factors including constituent anisotropy, volume fraction and thermal expansion, ply orientation, process cycle, and matrix cure chemistry. In this study, embedded strain gauges were employed to follow, in situ, the buildup of residual strains in carbon fiber‐reinforced laminates during cure. The data were compared to those from volumetric dilatometer studies to ascertain the fraction of resin shrinkage that contributed to residual stress buildup during cure. Based on earlier studies with single‐fiber model composites, the process cycle in each case was then varied to determine if the cycles optimized to minimize residual stresses for isolated fibers in an infinite matrix were applicable to the reduction of residual stresses in conventional multifiber composites. The results of these studies are reported here.     

Processing and properties of Cfibre/SiCfillers/SiOC composites using solvent free liquid polysiloxane as matrix source

Abstract

Carbon fibre reinforced SiOC composites (denoted as C_fibre/SiC_fillers/SiOC) were prepared by slurry coating and polymer infiltration pyrolysis (PIP) process. Low viscosity liquid polysiloxane (PSO) and SiC powder were combined at a 1∶1 weight ratio to produce a blend (S-PSO), which was employed as matrix source. Heat treated carbon fibre fabric was adopted as the reinforcement. The lamination process was determined on the basis of cure and rheology investigations on S-PSO. The effects of PIP cycles and temperature of heat treatment of the carbon fibre on the mechanical properties of C_fibre/SiC_fillers/SiOC were examined. The results indicate that composites using carbon fibres annealed at 1700°C as reinforcement reached a maximum flexural strength of 300 MPa after six PIP cycles. The resistance of the C_fibre/SiC_fillers/SiOC composite to oxidation was also evaluated. Without any protective coatings, the composite retained 60% of its strength after oxidation at 800°C for 3 h in a static air environment.     

Long fibre reinforced ceramics with active fillers and a modified intra-matrix bond based on the LPI process

Silicon-based preceramic polymers are attractive candidates for the manufacture of high temperature and corrosion resistant ceramics, particularly in regard to the formation of a ceramic matrix in long fibre reinforced ceramic matrix composites (CMCs). The manufacture of CMCs constitutes of the infiltration of fibre preforms followed by a subsequent crosslinking and pyrolysis of the Si-precursor, yielding an amorphous ceramic matrix. However, due to the inherent shrinkage of ceramic precursors, a high number of polymer impregnation and pyrolysis (PIP) cycles is required to obtain dense composites. Nevertheless, their microstructure is characterized by large interbundle pores which show a negative impact on the mechanical properties.In order to improve the performance of the long fibre reinforced CMCs as well as to accelerate the manufacturing process, a novel approach was investigated. Thereby, micro-sized powders of Al and Ti are used as active fillers. The powders were strewed between the fabric plies and infiltrated by the resin transfer moulding (RTM) technique. Since reactions with the polymer matrix are associated with a volume increase during pyrolysis, a more dense ceramic matrix is obtained.The processing of the CMCs employs the commercial polysilazanes CERASET SN and VL20 as preceramic precursors. The reinforcement constitutes of Tyranno SA fibres. To densify the composites, up to five PIP cycles were performed. CMC samples were aged in air to evaluate the impact of oxidation on microstructure and mechanical properties. Microstructural characterization was conducted using both optical and electron microscopy. The conversion of the filler particles was analysed by means of EDX and XRD.     

Continuous-time scheduling formulation for multipurpose batch plants

Short-term scheduling of batch processes is a complex combinatorial problem with remarkable impact on the total revenue of chemical plants. It consists of the optimal allocation of limited resources to tasks over time in order to manufacture final products following given batch recipes. This article addresses the short-term scheduling of multipurpose batch plants, using a mixed integer linear programming formulation based on the state-task network representation. It employs both single-grid and multi-grid continuous-time representations, derived from generalized disjunctive programming. In comparison to other multigrid scheduling models in the literature, the proposed multi-grid model uses no big-M constraints and leads to more compact mathematical models with strong linear relaxations, which often results in shorter computational times. The single-grid counterpart of the formulation is not as favorable, as it leads to weaker linear relaxations than the multi-grid approach and is not capable of handling changeover time constraints.     

The rheology and extrusion processing performance of wood/melamine composites

A modified melamine resin that exhibits both thermoplastic and thermoset behaviors was used as a matrix for wood plastic composites (WPCs). The thermoplastic melamine (TPM) resin exhibits a glass transition at approximately 34°C and continues to be thermally malleable until a crosslinking reaction develops with additional heating and an acid catalyst. Varying blends of TPM and wood flour were evaluated for their rheology and curing behavior using torque rheometry. WPC composites were manufactured with extrusion methods and final product properties determined. The torque rheometry results showed a highly dependent relationship of the curing behavior to the amount of wood flour utilized and temperature. Based upon the torque rheometry results, two extrusion platforms were developed to initiate the curing process; (1) cure within the die land and (2) post‐cure of the extrudate. The post‐cure procedure provided composites with higher mechanical properties. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131, 39858.     

Monitoring cure of autoclave-molded parts by dielectric analysis

A study was undertaken to determine the feasibility of using dielectric analysis as a means of monitoring and controlling cure of large closures during autoclave molding. In dielectric analysis, the dissipation factor (DF) and capacitance (C) of the sample are continuously monitored as a function of time, temperature, and frequency. Dissipation factor profiles were established for the suppliers' recommended cure cycle and for modified cure cycles, Good reproducibility was obtained in dissipation factor profiles on subsequent scaling up to production size (7 ft · 20 ft) autoclaves. Good correlation was also observed during production runs of fullscale closures. The effects of cure variables on the dissipation factor profiles and on the mechanical properties of the prepared laminates were analyzed for extent of correlation. Results of this study show: (1) dielectric analysis can be used to monitor autoclave cure of composites, and (2) within limits, process control may be feasible.     

Optimal curing for thermoset matrix composites: Thermochemical considerations

A design sensitivity analysis is used to optimize the applied wall temperature vs. time in autoclave curing for thermoset matrix composites. The calculation minimizes the cure time and obeys a maximum temperature constraint in the composite. The transient, coupled thermal and cure problem is solved by a finite element method. Design sensitivity information is extracted efficiently from this primal analysis, based on an analytical, direct differentiation approach. The sensitivities are then used with gradient‐based optimization techniques to systematically improve the curing process. The optimal cure cycles for different numbers of temperature dwells may be similar (for a 2 mm thick part) or very different (for a 4 cm thick part), depending on the nature of the problem. In the latter case a large reduction of cure time is obtained when a three‐dwell cure cycle is used, and the optimizer has more flexibility to adjust the cure cycle. This systematic optimization approach provides a powerful and practical means of optimizing composite manufacturing processes.     

Monitoring of Carbon Fiber/Polyamide Composites Processing by Rheological and Thermal Analyses

The use of continuous carbon fiber reinforced thermoplastic composites in the aerospace and automotive fields has increased due to their high performance. The hot compression molding process for the manufacture of the composites has attracted much interest due mainly to the high rate of production and quality of the finished parts. This work involves the use of rheological and thermal analyses for the optimization of the processing parameters related to the manufacture of carbon fabric/polyamide 6 and 6/6 by hot compression molding. The results show that the most adequate processing temperatures to be used in the hot compression molding are 250°C and 290°C for polyamides 6 and 6/6, respectively. The loss moduli value (G″) from DMA increased with the increment of the carbon fiber content in the glass transition temperatures, due to the reinforcement contribution. Therefore, the glass transition temperatures of all samples remained constant. The use of the established parameters based on the DSC, DMA, and rheological analyses favored the manufacture of composites with a homogeneous distribution of reinforcement and matrix as observed through optical microscopy analyses.     

A multiperiod nonlinear programming approach for operation of air separation plants with variable power pricing

Cryogenic air separation processes consume a large amount of electricity producing significant quantities of high purity gases. Rather than operating at a fixed steady state, it may be profitable to switch among different operating conditions because of variability of electrical prices and product demands. This article addresses the problem of determining the optimal daily multiperiod operating conditions for an air separation process under variable electricity pricing and uncertain product demands. The multiperiod nonlinear programming formulation includes a rigorous nonlinear model of the highly‐coupled process, and decision variables include the operating conditions within each period, as well as the transition times. Demand uncertainty is treated using the loss function included in the objective function and constraints on customer satisfaction levels. Solutions are obtained with high computational efficiency, allowing management to make informed decisions regarding operating strategies while considering the trade off between profitability and customer satisfaction levels. © 2010 American Institute of Chemical Engineers AIChE J, 2011     

Optimal Control of Continuous Infrared Dryers

In this work, the optimal control policies of radiant temperature versus dryer length are determined for the continuous, steady-state operation of infrared dryers. The optimal control objective is to minimize the product humidity subject to a mathematical model of infrared dryers as well as a set of process inequality constraints. A robust optimal control method based on genetic algorithms is applied. Multiple air injections are also considered. The optimal results show considerable reduction in product humidity. Comparisons with corresponding base cases (using maximum possible uniform radiant temperatures) indicate improvements greater than 50% with the application of optimal control policies.     

Optimal Control of Continuous Infrared Dryers

In this work, the optimal control policies of radiant temperature versus dryer length are determined for the continuous, steady-state operation of infrared dryers. The optimal control objective is to minimize the product humidity subject to a mathematical model of infrared dryers as well as a set of process inequality constraints. A robust optimal control method based on genetic algorithms is applied. Multiple air injections are also considered. The optimal results show considerable reduction in product humidity. Comparisons with corresponding base cases (using maximum possible uniform radiant temperatures) indicate improvements greater than 50% with the application of optimal control policies.     

Preparing recombinant single chain antibodies

A review of current processing practices in preparation of recombinant single chain antibody fragments is presented. Single chain antibody fragments which are superior to their Fab and IgG counterparts due to their higher affinity for target antigens while imposing minimal antigenicity in recipient hosts, have sparked breakthroughs in immunology and the medical field at large. The rapidly increasing market demand for pure single chain antibodies for research and therapeutic applications, necessitates viable manufacture routes that can produce large amounts of these antibodies efficiently and as cheaply as possible. Medium- to high-producing expression systems reported for recombinant single chain antibody production are reviewed, and their reported or potential success for efficient commercial-viable preparation of pure antibodies discussed. The effects of expression host system choice on product molecular constraints, ease of processing, and flowsheet design and scale-up are compared. It is concluded that there is no unique host system that can consistently yield high expression levels for a wide range of single chain antibodies; instead, product sequence and end application often dictate the optimum choice of expression host. Irrespective of host systems, adequate a priori design and engineering of the molecular construct supported by good biophysical understanding of the single chain fragment molecules, is a crucial pre-requisite for improved product stability and downstream recovery, which will favourably impact final product yield and functionality.     

Fresh water by reverse osmosis based desalination: simulation and optimisation

The reverse osmosis (RO) desalination process to make fresh water from seawater has been studied here. First, a model for the process is developed. Sensitivity of different operating parameters (feed flow rate, feed pressure) and design parameters (internal diameter, total number of tubes) on the recovery ratio are studied via repetitive simulation. Finally, an optimisation framework for the process is developed so as to maximize the recovery ratio or a profit function using different energy recovery devices, subjectto general constraints. The optimal operating parameters (feed flow rate, feed pressure) and design parameters (internal diameter, total number of tubes) are determined by solving the optimisation problem using an efficient successive quadratic programming (SQP) based method. The optimal values for the decision variables depend on the constraints introduced, and are also sensitive to variations in water and energy prices, as well as feed concentration. The use ofthe emerging energy recovery devices is widely justified, reporting much higher reductions in operating costs than the traditional technology used for this purpose. Using a pressure exchanger device, it is possible to reduce energy consumption by up to 50%.     

A novel model for multi-plant mixed heavy crude oils refinery planning

In this paper, multi-refinery using the same heavy crude oils as raw materials is studied, while a new nonlinear model for mixed heavy crude distillation is proposed. In practical crude distillation operation, the distillate yield and product distribution of distillation units are different due to their various equipment and operating parameters, even the same ratio of raw materials is provided, so different process models for multi-refinery planning is therefore required. For process modeling, the relationships between total yields and mixing ratio of different refineries were determined, which is combined with process simulation using production data. Then, the yields and properties of crude distillation unit (CDU) fractions were calculated with the use of true boiling point (TBP) curves and property curves respectively when the initial cutting temperatures were given. Finally, in order to maximize the economic benefit of distillation, the optimal product distribution and the best mixing ratio of crude oil were calculated under the constraints of different properties of fractions. Comparing to previous models, the proposed model takes the influence of different refinery parameters on production process into account, while avoiding the complex process for determining the cutting points, which is considered more effi-cient and more accurate with respect to heavy crude refinery. Model was successfully verified by a case study, allowing a significant improvement of the refinery profit to be achieved.