Aerospace medicine and biology: A continuing bibliography with indexes (supplement 324)

This bibliography lists 200 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during May, 1989. Subject coverage includes: aerospace medicine and psychology, life support systems and controlled environments, safety equipment, exobiology and extraterrestrial life, and flight crew behavior and performance

A comparison of processing techniques for producing prototype injection moulding inserts.

This project involves the investigation of processing techniques for producing low-cost moulding inserts used in the particulate injection moulding (PIM) process. Prototype moulds were made from both additive and subtractive processes as well as a combination of the two. The general motivation for this was to reduce the entry cost of users when considering PIM. PIM cavity inserts were first made by conventional machining from a polymer block using the pocket NC desktop mill. PIM cavity inserts were also made by fused filament deposition modelling using the Tiertime UP plus 3D printer. The injection moulding trials manifested in surface finish and part removal defects. The feedstock was a titanium metal blend which is brittle in comparison to commodity polymers. That in combination with the mesoscale features, small cross-sections and complex geometries were considered the main problems. For both processing methods, fixes were identified and made to test the theory. These consisted of a blended approach that saw a combination of both the additive and subtractive processes being used. The parts produced from the three processing methods are investigated and their respective merits and issues are discussed

Small business innovation research. Abstracts of completed 1987 phase 1 projects

Non-proprietary summaries of Phase 1 Small Business Innovation Research (SBIR) projects supported by NASA in the 1987 program year are given. Work in the areas of aeronautical propulsion, aerodynamics, acoustics, aircraft systems, materials and structures, teleoperators and robotics, computer sciences, information systems, spacecraft systems, spacecraft power supplies, spacecraft propulsion, bioastronautics, satellite communication, and space processing are covered

Reducing risk in pre-production investigations through undergraduate engineering projects.

This poster is the culmination of final year Bachelor of Engineering Technology (B.Eng.Tech) student projects in 2017 and 2018. The B.Eng.Tech is a level seven qualification that aligns with the Sydney accord for a three-year engineering degree and hence is internationally benchmarked. The enabling mechanism of these projects is the industry connectivity that creates real-world projects and highlights the benefits of the investigation of process at the technologist level. The methodologies we use are basic and transparent, with enough depth of technical knowledge to ensure the industry partners gain from the collaboration process. The process we use minimizes the disconnect between the student and the industry supervisor while maintaining the academic freedom of the student and the commercial sensitivities of the supervisor. The general motivation for this approach is the reduction of the entry cost of the industry to enable consideration of new technologies and thereby reducing risk to core business and shareholder profits. The poster presents several images and interpretive dialogue to explain the positive and negative aspects of the student process

ADAPTS: An Intelligent Sustainable Conceptual Framework for Engineering Projects

This paper presents a conceptual framework for the optimization of environmental sustainability in engineering projects, both for products and industrial facilities or processes. The main objective of this work is to propose a conceptual framework to help researchers to approach optimization under the criteria of sustainability of engineering projects, making use of current Machine Learning techniques. For the development of this conceptual framework, a bibliographic search has been carried out on the Web of Science. From the selected documents and through a hermeneutic procedure the texts have been analyzed and the conceptual framework has been carried out. A graphic representation pyramid shape is shown to clearly define the variables of the proposed conceptual framework and their relationships. The conceptual framework consists of 5 dimensions; its acronym is ADAPTS. In the base are: (1) the Application to which it is intended, (2) the available DAta, (3) the APproach under which it is operated, and (4) the machine learning Tool used. At the top of the pyramid, (5) the necessary Sensing. A study case is proposed to show its applicability. This work is part of a broader line of research, in terms of optimization under sustainability criteria.Telefónica Chair “Intelligence in Networks” of the University of Seville (Spain

The integration of hazard evaluation procedures and requirements engineering for safety-critical embedded systems

Although much work has been done on assessing safety requirements in programmable systems, one very important aspect, the integration of hazard evaluation procedures and requirements engineering, has been somewhat neglected. This thesis describes the derivation and application of a methodology, HAZAPS (HAZard Assessment in Programmable Systems). The methodology assists at the requirements stage in the development of safety-critical embedded systems. The objectives are to identify hazards in programmable systems, construct and model the associated safety requirements, and, finally, to assess these requirements. HAZAPS integrates safety engineering and software modelling techniques. The analysis of more than 300 computer related incidents provided the criteria used to identify, select and modify safety engineering techniques. [Continues.

LSTM-Based Wastewater Treatment Plants Operation Strategies for Effluent Quality Improvement

Wastewater Treatment Plants (WWTPs) are facilities devoted to managing and reducing the pollutant concentrations present in the urban residual waters. Some of them consist in nitrogen and phosphorus derived products which are harmful for the environment. Consequently, certain constraints are applied to pollutant concentrations in order to make sure that treated waters comply with the established regulations. In that sense, efforts have been applied to the development of control strategies that help in the pollutant reduction tasks. Furthermore, the appearance of Artificial Neural Networks (ANNs) has encouraged the adoption of predictive control strategies. In such a fashion, this work is mainly focused on the adoption and development of them to actuate over the pollutant concentrations only when predictions of effluents determine that violations will be produced. In that manner, the overall WWTP's operational costs can be reduced. Predictions are generated by means of an ANN-based Soft-Sensor which adopts Long-Short Term Memory cells to predict effluent pollutant levels. These are the ammonium (S-{NH,e}) and the total nitrogen (S-{Ntot,e}) which are predicted considering influent parameters such as the ammonium concentration at the entrance of the WWTP reactor tanks (S-{NH,po}), the reactors' input flow rate (Q-{po}), the WWTP recirculation rate (Q-{a}) and the environmental temperature (T-{as}). Moreover, this work presents a new multi-objective control scenario which consists in a unique control structure performing the reduction of S-{NH,e} and S-{Ntot,e} concentrations simultaneously. Performance of this new control approach is contrasted with other strategies to determine the improvement provided by the ANN-based Soft-Sensor as well as by the fact of being controlling two pollutants at the same time. Results show that some brief and small violations are still produced. Nevertheless, an improvement in the WWTPs performance w.r.t.The most common control strategies around 96.58% and 98.31% is achieved for S-{NH,e} and S-{Ntot,e}, respectively

The NASA SBIR product catalog

The purpose of this catalog is to assist small business firms in making the community aware of products emerging from their efforts in the Small Business Innovation Research (SBIR) program. It contains descriptions of some products that have advanced into Phase 3 and others that are identified as prospective products. Both lists of products in this catalog are based on information supplied by NASA SBIR contractors in responding to an invitation to be represented in this document. Generally, all products suggested by the small firms were included in order to meet the goals of information exchange for SBIR results. Of the 444 SBIR contractors NASA queried, 137 provided information on 219 products. The catalog presents the product information in the technology areas listed in the table of contents. Within each area, the products are listed in alphabetical order by product name and are given identifying numbers. Also included is an alphabetical listing of the companies that have products described. This listing cross-references the product list and provides information on the business activity of each firm. In addition, there are three indexes: one a list of firms by states, one that lists the products according to NASA Centers that managed the SBIR projects, and one that lists the products by the relevant Technical Topics utilized in NASA's annual program solicitation under which each SBIR project was selected

Graphene-based flexible sensors towards electronic wearables

Flexible electronics and wearable devices have attracted considerable attention because they produce mechanical liberty, in terms of flexibility and stretchability that can enable the possibility of a wide range of new applications. The term “wearable electronics” can be used to define devices that can be worn or mated with the sensed surface to continuously monitor signals without limitations on mechanical deformability of the devices and electronic performance of the functional materials. The use of polymeric substrates or other nonconventional substrates as base materials brings novel functionalities to sensors and other electronic devices in terms of being flexible and light weight. Conductive nanomaterials, such as carbon nanotubes and graphene have been utilized as functional materials for flexible electronics and wearable devices. Graphene has specifically been considered for producing next-generation sensors due to its impressive electrical and mechanical properties and a result, incorporation of flexible substrates and graphene-based nanomaterials has been widely utilized to form versatile flexible sensors and other wearable devices through use of different fabrication processes. Creation of a large-scale, simple, high-resolution and cost-effective technique that overcomes fabrication limitations and supports production of flexible graphene-based sensors with high flexibility and stretch ability is highly demanding. Soft lithography can be merged with a mechanical exfoliation process using adhesive tape followed by transfer printing to form a graphene sensor on a desired final substrate. In situ microfluidic casting of graphene into channels is another promising platform driving the rapid development of flexible graphene sensors and wearable devices with a wide dynamic detection range. Selective coating of graphene-based nanomaterials (e.g. graphene oxide (GO)) on flexible electrode tapes can, because of its flexibility and adhesive features, be used to track relative humidity (RH) variations at the surface of target surfaces. This thesis describes the design and development of flexible and wearable strain, pressure and humidity sensors based on a novel tape-based cost-effective patterning and transferring technique, an in situ microfluidic casting method, and a novel selective coating technique for graphene-based nanomaterials. First of all, we present a tape-based graphene patterning and transferring approach to production of graphene sensors on elastomeric substrates and adhesive tapes. The method utilizes the work of adhesion at the interface between two contacting materials as determined by their surface energies to pattern graphene on PDMS substrate and transfer it onto a target tape. We have achieved patterning and transferring method with the features of high pattern spatial resolution, thickness control, and process simplicity with respect to functional materials and pattern geometries. We have demonstrated the usage of flexible graphene sensors on tape to realize interaction with structures, humans, and plants for real-time monitoring of important signals. Secondly, we present a helical spring-like piezo resistive graphene sensor formed within a microfluidic channel using a unique and easy in situ microfluidic casting method. Because of its helical shape, the sensor exhibits a wide dynamic detection range as well as mechanical flexibility and stretch ability. Finally, we present a flexible GO-based RH sensor on an adhesive polyimide thin film realized by selectively coating and patterning GO at the surface of Au Interdigitated electrodes (IDEs) and subsequently peeling the device from a temporary PDMS film. Real-time monitoring of the water movement inside the plant has been demonstrated by installing GO-based RH sensor at the surfaces of different plant leaves

A novel sensor measuring local voidage profile inside a fluidised bed reactor

Liquid-solid fluidisation is frequently encountered in drinking water treatment processes, often to obtain a large liquid-solid interfacial surface area. A large surface area is crucial for optimal seeded crystallisation in full-scale softening reactors. Due to crystallisation, particles grow and migrate to a lower zone in the reactor which leads to a stratified bed. Larger particles adversely affect the surface area. To maintain optimal process conditions in the fluidised beds, information is needed about the distribution of particle size, local voidage and available surface area, over the reactor height. In this work, a sensor is developed to obtain the hydraulic state gradient, based on Archimedes’ principle. A cylindrical heavy object is submerged in the fluidised bed and lowered gradually while its weight is measured at various heights using a sensitive force measuring device. Based on accurate fluidisation experiments with calcite grains, the voidage is determined and a straightforward empirical model is developed to estimate the particle size as a function of superficial fluid velocity, kinematic viscosity, suspension density, voidage and particle density. The surface area and specific space velocity can be estimated accordingly, which represent key performance indicators regarding the hydraulic state of the fluidised bed reactor. The prediction error for voidage is 5 ± 2 % and for particle size 9 ± 4 %. The newly developed soft sensor is a more time-effective method for obtaining the hydraulic state in full-scale liquid-solid fluidised bed reactors