Capital costs design variables

In order to minimize utility costs, design variables of the membrane unit can be chosen to give better separation. For example, a larger membrane area will lead to more separation for a given feed flowrate and permeate pressure. This may lead to a reduction in condenser and reboiler duties of the associated column. While there is a decrease in utility cost of the column, there is a corresponding increase in the capital cost of the membrane. This results... 

The rate of a chemical reaction is influenced by pressure, temperature, concentration of reactants, kinetic factors such as agitation, and the presence of a catalyst. Since the viability of a plant depends not only on reaction efficiencies but also on the capital cost factor and the cost of maintenance, it may be more economic to alter a process variable in order that a less expensive material of construction can be used. The flexibility which the process designer has in this respect depends on how sensitive the reaction efficiency is to a change in the variable of concern to the materials engineer. 

Suppose you want to design a hydrocarbon piping system in a plant between two points with no change in elevation and want to select the optimum pipe diameter that minimizes the combination of pipe capital costs and pump operating costs. Prepare a model that can be used to carry out the optimization. Identify the independent and dependent variables that affect the optimum operating conditions. Assume the fluid properties (/i, p) are known and constant, and the value of the pipe length (L) and mass flowrate (m) are specified. In your analysis use the following process variables pipe diameter (D), fluid velocity (v), pressure drop (A/ ), friction factor (/). 

The estimation of operating and capital costs is an important facet of process design and optimization. In the absence of firm bids or valid historical records, you can locate charts, tables, and equations that provide cost estimates from a wide variety of sources based on given values of the design variables. 

A pilot-scale demonstration remediating harbor sediment was conducted 1 year before the SITE demonstration. Based on the pilot-scale demonstration, the processing costs for a fuU-scale, 110-ton/day unit were projected to be 230/ton (September 1992 U.S. dollars). It is assumed that the unit will be down approximately 30% of the time for maintenance and design improvements in the first year of operation. Based on this system availability, 28,105 tons can be processed in one year. This cost included estimates for variable costs, fixed costs, and deprecia-tion/insurance. Variable costs include diesel fuel for a mobile generator, hydrogen, and caustic. Fixed costs include labor diesel fuel for pumps, heaters, process equipment, and instrumentation propane, water and sewer and parts and supplies. Depreciation/insurance costs include capital cost depreciated over a 3-year period, general insurance costs, and pollution liabihty insurance. This analysis does not include costs for setup and demobilization (D128007, pp. 5.12-5.14). 

The performance ratio or heat economy is a result of the selection of design variables previously discussed, and is not a variable as such. Lines of constant capital cost per daily gallon of capacity are also included in Figure 3. Capital costs have been based on plant capacities in a range of 25,000,000 to 60,000,000 gallons a day and a velocity in the evaporator tubes of 5 feet per second. These lines of constant capital cost per daily gallon are a result of cross plotting the results obtained in the optimization study. 

The specification of a control scheme and the associated instrumentation for a chemical plant should satisfy several main objectives. First, the plant should operate at all times in a safe manner. Dangerous situations should be detected as early as possible and appropriate action initiated, also the process variables should be maintained within safe operating limits. Second, the plant should operate at the lowest cost of production. Finally, the production rate and the product quality must be maintained within specified operating limits. These objectives may be conflicting, and the final control scheme to be adopted is based upon a realistic and acceptable compromise between the various factors. The main conflict is between the need to design and operate as safe a plant as possible and the desire to produce the chemical at the lowest cost. Safe plant operation can be expensive, both in terms of the capital cost of instrumentation and the annual operating costs, e.g. maintenance. 

Remember this is for a fixed per-pass conversion and inlet composition and flowrate. If the desired conversion is decreased, the inlet temperature can be increased and the reactor size reduced. Of course, this means that more unreacted material in the reactor effluent must be recovered and recycled. Keep in mind the difference between the per pass conversion, which is a crucial design optimization variable, and the overall conversion of the entire process, which is typically quite close to 100% because the cost of raw materials imposes a severe economic penalty on a process with low overall conversion. A lower per-pass conversion translates into a higher recycle flow with its associated higher energy and capital costs. But chemical process economics usually dictate that capital investment can be justified to save energy, and both energy and capital can be expended to reduce losses of raw materials and/or products. 

As the operating and capital costs grow with V by an economic factor less than 1, a column with large V will always be profitable (Diwekar et al., 1989) and the problem becomes unbounded (also proven in Logsdon et al., 1990). Hence V is also fixed a priori. This leaves just N (the number of internal ideal separation stages or plates) as the only design variable to be optimised (UP = N ). Out of all possible operation decision variables, it is common to specify the mole fraction of key components in main-cuts and sometimes some recoveries or amounts for off-cuts. Assuming NSP such specifications are made, there are (NV + 1 - NSP) outer optimisation problem decision variables. 

The present method can be extended easily to other applications. For instance, a cost function involving operating and capital expenses, and product distribution may be minimized with respect to operating and design variables. 

Table Vll describes the class of heat exchanger chosen and summarizes the design equations and the capital cost equation. The cost of the heat exchanger, expressed in terms of geometric variables, (measured in feet) is given by ...

Cost Estimation. The capital costing equations used in the cogeneration problem have been designed to yield approximate capital and maintenance expenditures and to reflect the consequence of changing the system s variables on these costs. The form of these equations expresses equipment costs in terms of stream and performance variables. In all cases a capital recovery factor is used to account for the cost of capital (i = 15%) and estimated useful life (n = 40 years). 

Once the necessary expressions for the entropy productions are developed, the thermodynamic variables must be transformed into the relevant process design variables. These various equations can then be coupled with capital cost expressions to allow system optimization by any current technique (Lagrange multipliers, surrogatic worth trade-off, ). 

The first term in this equation reflects fuel costs and alternatively could be expressed in terms of the system inefficiencies and the system utility costs. The second term is indicative of the capital investment. However, the system inefficiencies and the capital investment are functions of the design variables. 

Optimization Procedure. Given a set of design variables (a working design), capital cost equations as functions of the design variables (9), the unit costs of utilities, and Equations 33-35, the Second-Law based optimization may be performed. 

The main variable of design for a CSTR is the hydraulic retention time (HRT), which represents the ratio between volume and flow rate, and it is a measure of the average length of time that a soluble compound remains in the reactor. Capital costs are related to HRT, as this variable directly influences reactor volume [83]. HRT can be calculated by means of a mass balance of the system in that case, kinetic parameters are required. Some authors obtained kinetic models from batch assays operating at the same reaction conditions, and applied them to obtain the HRT in continuous operation [10, 83, 84]. When no kinetic parameters are available, HRT can be estimated from the time required to complete the reaction in a discontinuous process. One must take into account that the reaction rate in a continuous operation is slower than in batch systems, due to the low substrate concentration in the reactor. Therefore, HRT is usually longer than the total time needed in batch operation [76]. 

An additional complication in formulating the objective function is the quantification of uncertainty. Economic objective functions are generally very sensitive to the prices used for feeds, raw materials, and energy, and also to estimates of project capital cost. These costs and prices are forecasts or estimates and are usually subject to substantial error. Cost estimation and price forecasting are discussed in Sections 6.3 and 6.4. There may also be uncertainty in the decision variables, either from variation in the plant inputs, variations introduced by unsteady plant operation, or imprecision in the design data and the constraint equations. Optimization under uncertainty is a specialized subject in its own right and is beyond the scope of this book. See Chapter 5 of Diwekar (2003) for a good introduction to the subject. 

On this basis, a cost or value of the available energy flows at the various junctures within the system can be determined (iteratively). Then if, for example, a particular component needs to deliver some specified output, knowing the unit cost of the availability supplied to the component, the component and its operating conditions can be selected (or designed) so that the total costs—of availability supplied thereto and of capital costs thereof, (etc.)—can be minimized. Typical parameters (decision variables) of a component which can be adjusted in order to attain the optimum system are efficiency, operating pressure and temperature, speed, and so on and so forth. 

Please write a brief report discussing how the design variables (catalyst size, inlet pressure, bed length) affect both the capital and operating costs of this process. What additional information would you require to perform a better design ... 

Case Design/Decision variables Utility cost savings ( /yr) Annualized capital cost of retrofitting ( /yr)... 

Year Percentage of Design Capacity Sales Capital Costs Working Capital Variable Costs Fixed Costs Depredation Allowance Depletion Allowance Taxable Income Income Tax Costs Net Earnings Annual Cash Flow Cumulative Net Present Value at 15.0%... 

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