Black-box technique

What makes our approach rather different from the mainstream international cleaner production (CP) movement is the desire to abolish the dominating "black-box" techniques. Instead of regarding a production facility as no more than a given set of benign inputs and polluting outputs, we insist that one should seek the best ways to affect a prospective cleaner object within the "black box". 

Engineers like to approach process problems with a black box technique. That is, any system or piece of equipment operating under steady-state conditions can be represented by a box with input and output streams consisting of mass flows and/or energy. Figure 3.3 illustrates the concept. 

Figure 3.3 Process operations or equipment can be represented by a generalized flow process known as the black box technique.

Raman spectroscopy has its main strength in the combination of a fairly high chemical selectivity and a true remote sensing capability. In comparison, NIR has been used extensively in the manufacturing industry due to its ruggedness and simplicity with respect to interfacing of probes to process vessels. However, due to fairly poor spectral selectivity it has to be paired with multivariate data evaluation and is thus sometimes considered as a black box technique. Mid-IR, on the other hand, offers a high selectivity and is also well established... 

A variety of rules have been developed to control the movement and adaptation of the simplex, of which the most famous set is due to Nelder and Mead (Olsson and Nelson, 1975). The Nelder-Mead simplex procedure has been successfully used for a wide range of optimization problems and, due to its simple implementation, is amongst the most widely used of all optimization techniques. Importantly for the current application, simplex optimization is a black-box technique since it uses only the comparative values of the function at the vertices of the simplex to advance the position of the simplex, and it therefore requires no knowledge of the underlying mathematical function. It is also well suited to the optimization of expensive functions since as few as one new measurement is needed to advance the simplex one step. In its usual form, simplex optimization is suitable only for unconstrained optimization, but effective constrained versions have also been developed (Parsons et al., 2007 ... 

A. Saltelli and T. Homma, Sensitivity Analysis for Model Output Performance of Black Box Techniques on Three International Benchmark Exercises, Comput. Stat. Data Anal. 13 (1992) 73-94. 

TG cannot be considered as a black box technique where fingerprint curves are obtained irrespective of the experimental conditions. Establishing the optimum conditions for TG analysis frequently requires many preliminary tests. It is essential for accurate TG work that the experimental conditions be recorded and that within a given series of samples the optimum conditions be standardized and maintained throughout the course of the experiments. Only then can TG curves from different experiments be compared in a meaningful way. 

In the literature, there is much information about the adsorption of small molecules on Pt, Rh, and Pd (see, e.g., [3,13]) on such samples as single-crystal surfaces and supported metal catalysts. The FEM enables us to bridge the gap between these two extremes, because it allows a very high resolution look at sharp metal tips ( 1000 A), that are in many cases only about one order of magnitude larger than in a supported catalyst. This surface science approach, for example, permits the study of the interaction of adjacent planes on the reactivity of one another. Many of the oscillatory reactions seen on field emitters in situ are examples of such interplay of the different nanosized surfaces present [11,14]. This interaction can obviously not be studied with large single crystals and is lost in the black box techniques of the macroscopic world of the supported catalysts. 

In practical applications a neural network can be used when the exact model is not known. It is a good example of a black-box technique. By no means, however, should the neural network be seen as the ultimate solution for problems with undefined or only partially defined models. The main reason is that it gives no additional information about the physical relationships and thus it will give no physical insight into the process. 

A more complex fuzzy relationship can provide a better description. However, the observed behavior of the net growth rate is not so complex that a more complex fuzzy relationship is justified from a transparency point of view. A final evaluation of the fuzzy model should be done after integration in the hybrid model structure. Although fuzzy logic is a black box technique, a posteriori analysis of the model shows that the three rules represent three phases during a batch. 

Because of the flexibility of choosing active orbitals for the CASSCF wave function CASPT2 is not a black-box technique. 

HyperChem should not be viewed as a black box that computes only what its designers thought correct. It has an open architecture that makes it possible to customize it many ways. As far as is possible, the parameters of molecular mechanics and semi-empirical calculations are in the user s hands. As the techniques of software engineering advance and our expertise in building new... 

The time that a molecule spends in a reactive system will affect its probability of reacting and the measurement, interpretation, and modeling of residence time distributions are important aspects of chemical reaction engineering. Part of the inspiration for residence time theory came from the black box analysis techniques used by electrical engineers to study circuits. These are stimulus-response or input-output methods where a system is disturbed and its response to the disturbance is measured. The measured response, when properly interpreted, is used to predict the response of the system to other inputs. For residence time measurements, an inert tracer is injected at the inlet to the reactor, and the tracer concentration is measured at the outlet. The injection is carried out in a standardized way to allow easy interpretation of the results, which can then be used to make predictions. Predictions include the dynamic response of the system to arbitrary tracer inputs. More important, however, are the predictions of the steady-state yield of reactions in continuous-flow systems. All this can be done without opening the black box. 

Spectroscopic techniques, carried out in in situ and operando conditions, obviously represent powerful tools for the description of the reactions and the catalysts in running conditions. In fact, the exigency of the scientist to look at the chemical process at a molecular level cannot only address the traditional kinetics modelling, where the reactor itself behaves as a black box. The use of spectroscopy allows monitoring the catalytic material under duty, directly revealing species and transformations, which can then support the hypothesis made for mathematical calculations applied to a kinetic model [1],... 

Stochastic or probabilistic techniques can be applied to either the moisture module, or the solution of equation (3) — or for example the models of Schwartz Crowe (13) and Tang et al. (16), or can lead to new conceptual model developments as for example the work of Jury (17). Stochastic or probabilistic modeling is mainly aimed at describing breakthrough times of overall concentration threshold levels, rather than individual processes or concentrations in individual soil compartments. Coefficients or response functions and these models have to be calibrated to field data since major processes are studied via a black-box or response function approach and not individually. Other modeling concepts may be related to soil models for solid waste sites and specialized pollutant leachate issues (18). 

Figure 8 Instrumental setup used to implement the CAR technique in CL kinetic-based determinations according to the detection system used a spectrofluorimeter or a black box including a PMT.

Errors in trace analyses are usually hidden to all except those intimately involved in the sample collection and, later, in the bench analysis. In chromatography, especially, it is too easy to hide behind uncertain work because published research does not concern itself with exactly how the chromatographer makes his quantitative decisions. Today, with the advent of the microprocessor and with the use of black box instruments, the chromatographer knows even less about his calibration graph or line, or the error associated with it. In these instruments, a single point and the origin may determine the calibration graph. Similar problems exist in other modern instrumental analysis techniques. 

We have combined classical statistical techniques with graphical techniques which allow the user a more direct Interaction with the data than would be achieved by a "black box operation of purely mathematical techniques. 

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