9 resultados para Telemetry of process variables
em Universidad de Alicante
Resumo:
This paper introduces a new mathematical model for the simultaneous synthesis of heat exchanger networks (HENs), wherein the handling pressure of process streams is used to enhance the heat integration. The proposed approach combines generalized disjunctive programming (GDP) and mixed-integer nonlinear programming (MINLP) formulation, in order to minimize the total annualized cost composed by operational and capital expenses. A multi-stage superstructure is developed for the HEN synthesis, assuming constant heat capacity flow rates and isothermal mixing, and allowing for streams splits. In this model, the pressure and temperature of streams must be treated as optimization variables, increasing further the complexity and difficulty to solve the problem. In addition, the model allows for coupling of compressors and turbines to save energy. A case study is performed to verify the accuracy of the proposed model. In this example, the optimal integration between the heat and work decreases the need for thermal utilities in the HEN design. As a result, the total annualized cost is also reduced due to the decrease in the operational expenses related to the heating and cooling of the streams.
Resumo:
This paper presents a new mathematical programming model for the retrofit of heat exchanger networks (HENs), wherein the pressure recovery of process streams is conducted to enhance heat integration. Particularly applied to cryogenic processes, HENs retrofit with combined heat and work integration is mainly aimed at reducing the use of expensive cold services. The proposed multi-stage superstructure allows the increment of the existing heat transfer area, as well as the use of new equipment for both heat exchange and pressure manipulation. The pressure recovery of streams is carried out simultaneously with the HEN design, such that the process conditions (streams pressure and temperature) are variables of optimization. The mathematical model is formulated using generalized disjunctive programming (GDP) and is optimized via mixed-integer nonlinear programming (MINLP), through the minimization of the retrofit total annualized cost, considering the turbine and compressor coupling with a helper motor. Three case studies are performed to assess the accuracy of the developed approach, including a real industrial example related to liquefied natural gas (LNG) production. The results show that the pressure recovery of streams is efficient for energy savings and, consequently, for decreasing the HEN retrofit total cost especially in sub-ambient processes.
Resumo:
Although hydrothermal carbonization of biomass components is known to be mainly governed by reaction temperature, consistent reports on the effect and statistical significance of process conditions on hydrochar properties are still lacking. The objective of this research was to determine the importance and significance of reaction temperature, retention time and solid load on the properties of hydrochar produced from an industrial lignocellulosic sludge residue. According to the results, reaction temperature and retention time had a statistically significant effect on hydrochar ash content, solid yield, carbon content, O/C-ratio, energy densification and energy yield as reactor solid load was statistically insignificant for all acquired models within the design range. Although statistically significant, the effect of retention time was 3–7 times lower than that of reaction temperature. Predicted dry ash-free solid yields of attained hydrochar decreased to approximately 40% due to the dissolution of biomass components at higher reaction temperatures, as respective oxygen contents were comparable to subbituminous coal. Significant increases in the carbon contents of hydrochar led to predicted energy densification ratios of 1–1.5 with respective energy yields of 60–100%. Estimated theoretical energy requirements of carbonization were dependent on the literature method used and mainly controlled by reaction temperature and reactor solid load. The attained results enable future prediction of hydrochar properties from this feedstock and help to understand the effect of process conditions on hydrothermal treatment of lignocellulosic biomass.
Resumo:
This multidisciplinary study concerns the optimal design of processes with a view to both maximizing profit and minimizing environmental impacts. This can be achieved by a combination of traditional chemical process design methods, measurements of environmental impacts and advanced mathematical optimization techniques. More to the point, this paper presents a hybrid simulation-multiobjective optimization approach that at once optimizes the production cost and minimizes the associated environmental impacts of isobutane alkylation. This approach has also made it possible to obtain the flowsheet configurations and process variables that are needed to manufacture isooctane in a way that satisfies the above-stated double aim. The problem is formulated as a Generalized Disjunctive Programming problem and solved using state-of-the-art logic-based algorithms. It is shown, starting from existing alternatives for the process, that it is possible to systematically generate a superstructure that includes alternatives not previously considered. The optimal solution, in the form a Pareto curve, includes different structural alternatives from which the most suitable design can be selected. To evaluate the environmental impact, Life Cycle Assessment based on two different indicators is employed: Ecoindicator 99 and Global Warming Potential.
Resumo:
Gasoline coming from refinery fluid catalytic cracking (FCC) unit is a major contributor to the total commercial grade gasoline pool. The contents of the FCC gasoline are primarily paraffins, naphthenes, olefins, aromatics, and undesirables such as sulfur and sulfur containing compounds in low quantities. The proportions of these components in the FCC gasoline invariable determine its quality as well as the performance of the associated downstream units. The increasing demand for cleaner and lighter fuels significantly influences the need not only for novel processing technologies but also for alternative refinery and petrochemical feedstocks. Current and future clean gasoline requirements include increased isoparaffins contents, reduced olefin contents, reduced aromatics, reduced benzene, and reduced sulfur contents. The present study is aimed at investigating the effect of processing an unconventional refinery feedstock, composed of blend of vacuum gas oil (VGO) and low density polyethylene (LDPE) on FCC full range gasoline yields and compositional spectrum including its paraffins, isoparaffins, olefins, napthenes, and aromatics contents distribution within a range of operating variables of temperature (500–700 °C) and catalyst-feed oil ratio (CFR 5–10) using spent equilibrium FCC Y-zeolite based catalyst in a FCC pilot plant operated at the University of Alicante’s Research Institute of Chemical Process Engineering (RICPE). The coprocessing of the oil-polymer blend led to the production of gasoline with very similar yields and compositions as those obtained from the base oil, albeit, in some cases, the contribution of the feed polymer content as well as the processing variables on the gasoline compositional spectrum were appreciated. Carbon content analysis showed a higher fraction of the C9–C12 compounds at all catalyst rates employed and for both feedstocks. The gasoline’s paraffinicity, olefinicity, and degrees of branching of the paraffins and olefins were also affected in various degrees by the scale of operating severity. In the majority of the cases, the gasoline aromatics tended toward the decrease as the reactor temperature was increased. While the paraffins and iso-paraffins gasoline contents were relatively stable at around 5 % wt, the olefin contents on the other hand generally increased with increase in the FCC reactor temperature.
Resumo:
Degree in nursing from the Universitat Jaume I (UJI) maintains the continuity of learning with an integrated learning methodology (theory, simulated practice and clinical practice). The objective of this methodology is to achieve consistency between the knowledge, abilities and skills acquired in the classroom, laboratory and clinic to ensure skills related. Reference Nurse is a key figure in this process, you receive accredited training on Educational Methods, assessment of competence, and Evidence-Based Practice that plays the role of evaluating in conjunction with the subjects. It does not perceive economic remuneration. The main objective of this study is to determine the level of satisfaction of clinical nurses on the Nurses Training Program Reference in UJI (Castellon- Spain). A cross sectional study was performed and conducted on 150 nurses. 112 questionnaires were completed, collected and analysed at the end of training. The survey consists of 12 items measured with the Likert scale with 5 levels of response and two open questions regarding the positive and negative aspects of the course and to add in this formation. The training is always performed by the same faculty and it's used four sessions of 2012. We perform a quantitative analysis of the variables under study using measures of central tendency. The completion rate of the survey is 95.53% (n=107). Anonymity rate of 54,14% The overall satisfaction level of training was 3.65 (SD = 0.89) on 5 points. 54.2% (n = 58) of the reference nurses made a contribution in the open questions described in the overall results. The overall satisfaction level can be considered acceptable. It is considered necessary to elaborate a specific survey to detect areas of improvement of nurse training program reference and future recruitment strategies. The main objective of the present work is the selection and integration of different methodologies among those applicable within the framework of the European Higher Education Area to combine teaching methods with high implication from both lecturers and students.
Resumo:
This paper introduces a new optimization model for the simultaneous synthesis of heat and work exchange networks. The work integration is performed in the work exchange network (WEN), while the heat integration is carried out in the heat exchanger network (HEN). In the WEN synthesis, streams at high-pressure (HP) and low-pressure (LP) are subjected to pressure manipulation stages, via turbines and compressors running on common shafts and stand-alone equipment. The model allows the use of several units of single-shaft-turbine-compressor (SSTC), as well as helper motors and generators to respond to any shortage and/or excess of energy, respectively, in the SSTC axes. The heat integration of the streams occurs in the HEN between each WEN stage. Thus, as the inlet and outlet streams temperatures in the HEN are dependent of the WEN design, they must be considered as optimization variables. The proposed multi-stage superstructure is formulated in mixed-integer nonlinear programming (MINLP), in order to minimize the total annualized cost composed by capital and operational expenses. A case study is conducted to verify the accuracy of the proposed approach. The results indicate that the heat integration between the WEN stages is essential to enhance the work integration, and to reduce the total cost of process due the need of a smaller amount of hot and cold utilities.
Resumo:
The present study examined the predictive effects of intellectual ability, self-concept, goal orientations, learning strategies, popularity and parent involvement on academic achievement. Hierarchical regression analysis and path analysis were performed among a sample of 1398 high school students (mean age = 12.5; SD =.67) from eight education centers from the province of Alicante (Spain). Cognitive and non-cognitive variables were measured using validated questionnaires, whereas academic achievement was assessed using end-of-term grades obtained by students in nine subjects. The results revealed significant predictive effects of all of the variables. The model proposed had a satisfactory fit, and all of the hypothesized relationships were significant. These findings support the importance of including non-cognitive variables along with cognitive variables when predicting a model of academic achievement.
Resumo:
The Surface Renewal Theory (SRT) is one of the most unfamiliar models in order to characterize fluid-fluid and fluid-fluid-solid reactions, which are of considerable industrial and academicals importance. In the present work, an approach to the resolution of the SRT model by numerical methods is presented, enabling the visualization of the influence of different variables which control the heterogeneous overall process. Its use in a classroom allowed the students to reach a great understanding of the process.