Sensor Selection and Optimization for Health Assessment of Aerospace Systems

Aerospace systems are developed similarly to other large-scale systems through a series of reviews, where designs are modified as system requirements are refined. For space-based systems few are built and placed into service. These research vehicles have limited historical experience to draw from and formidable reliability and safety requirements, due to the remote and severe environment of space. Aeronautical systems have similar reliability and safety requirements, and while these systems may have historical information to access, commercial and military systems require longevity under a range of operational conditions and applied loads. Historically, the design of aerospace systems, particularly the selection of sensors, is based on the requirements for control and performance rather than on health assessment needs. Furthermore, the safety and reliability requirements are met through sensor suite augmentation in an ad hoc, heuristic manner, rather than any systematic approach. A review of the current sensor selection practice within and outside of the aerospace community was conducted and a sensor selection architecture is proposed that will provide a justifiable, dependable sensor suite to address system health assessment requirements

Determination of chlorinated solvents in industrial water and wastewater by DAI–GC–ECD

A very simple and quick analytical method, based on direct aqueous injection, for determination of halogenated solvents in refinery water and wastewater, is described. There is a need to determine halogenated solvents in refinery water streams, because they may originate from several processes. There is also a need to develop methods enabling VOX to be determined in samples containing oil fractions. The method described enables simultaneous determination of 26 compounds with low detection limits (sub-μg L−1) and excellent precision, especially for highly halogenated solvents. The matrix effects of four types of sample were evaluated—the method seemed to be relatively insensitive to variations in matrix composition. Deuterated 1,2-dichloroethane was used as internal standard and surrogate compound in quantitative analysis; application of isotopically labelled compounds is rarely reported when non-mass spectrometric detectors are used for analysis. Analysis of real samples showed that the most frequently detected compounds were dichloromethane and 1,2-dichloroethane

Water Network Optimization with Wastewater Regeneration Models

The conventional water network synthesis approach greatly simplifies wastewater treatment units by using fixed recoveries, creating a gap for their applicability to industrial processes. This work describes a unifying approach combining various technologies capable of removing all the major types of contaminants through the use of more realistic models. The following improvements are made over the typical superstructure-based water network models. First, unit-specific shortcut models are developed in place of the fixed contaminant removal model to describe contaminant mass transfer in wastewater treatment units. Shortcut wastewater treatment cost functions are also incorporated into the model. In addition, uncertainty in mass load of contaminants is considered to account for the range of operating conditions. Furthermore, the superstructure is modified to accommodate realistic potential structures. We present a modified Lagrangean-based decomposition algorithm in order to solve the resulting nonconvex mixed-integer nonlinear programming (MINLP) problem efficiently. Several examples are presented to illustrate the effectiveness and limitations of the algorithm for obtaining the global optimal solutions.The authors would like to acknowledge financial support from the National Science Foundation for financial support under grant CBET-1437668, the program “Estancias de movilidad en el extranjero “Jose Castillejo” para jóvenes doctores” (JC2011-0051) of the Spanish Ministerio de Educación, and from the University of Alicante (GRE11-19)