Richard W. Tock

Study of the effect of sliding velocity on the frictional properties of nonwoven fabric substrates

Frictional properties of nonwoven substrates have been investigated using a sliding friction apparatus. Nonwoven substrates were developed using a modern needle-punching nonwoven technology. The experiment was conducted over a range of applied normal loads. The study was aimed at understanding the effect of testing speeds on the frictional properties of needle-punched nonwoven substrates. Frictional properties were characterized using friction factors, C, n and R. Results indicate that as the speed of the testing increased, frictional resistance increased.

A Simple Neural Network for Estimating Emission Rates of Hydrogen Sulfide and Ammonia from Single Point Sources

Neural networks have shown tremendous promise in modeling complex problems. This work describes the development and validation of a neural network for the purpose of estimating point source emission rates of hazardous gases. This neural network approach has been developed and tested using experimental data obtained for two specific air pollutants of concern in West Texas, hydrogen sulfide and ammonia. The prediction of the network is within 20% of the measured emission rates for these two gases at distances of less than 50 m. The emission rate estimations for ground level releases were derived as a function of seven variables: downwind distance, crosswind distance, wind speed, downwind concentration, atmospheric stability, ambient temperature, and relative humidity. A backpropagation algorithm was used to develop the neural network and is also discussed here. The experimental data were collected at the Wind Engineering Research Field Site located at Texas Tech University in Lubbock, Texas. Based on the results of this study, the use of neural networks provides an attractive and highly effective tool to model atmospheric dispersion, in which a large number of variables interact in a nonlinear manner.

Estimation of point-source emissions of hydrogen sulfide and ammonia using a modified Pasquill-Gifford approach

Abstract Estimation of point-source emissions based on measured downwind concentrations and known meteorology is a challenging task. A facility to study atmospheric dispersion of hazardous gases has been designed and implemented at the Wind Engineering Research Field Laboratory (WERFL) at Texas Tech University in Lubbock, Texas. The field lab features a 48.5 m (160 ft) meteorological tower which can monitor wind speed at six heights, wind direction and vertical temperature gradients using temperature measurements at two elevations. The relative humidity and barometric pressure can also be monitored. A description of the facility and its features are provided in this paper. In this work, the Pasquill-Gifford (PG) model was modified to provide predictions of emission rates for two hazardous gases; hydrogen sulfide (H 2 S) and ammonia (NH 3 ). Two mathematical manipulations of the PG model were used to refine estimates of emission rates of H 2 S and NH 3 based on experimental field data. The first modified PG approach was based on an empirical correction to the Gaussian model, and was evaluated only for direct downwind distances and neutral atmospheric stability conditions. The second approach was based on an improved procedure for estimation of the specific dispersion coefficients for H 2 S and NH 3 required in the PG model. These new dispersion coefficients were estimated from experimental data obtained in the field under both neutral and stable atmospheric conditions.

Airbag fabric material modeling of nylon and polyester fabrics using a very simple neural network architecture

The material properties of engineering fabrics that are used to manufacture airbags can not be modeled easily by the available nonlinear elastic–plastic shell elements. A nonlinear membrane element that incorporates an elaborate tissue material model has been widely used by the auto industry for the airbag simulation studies. This model is highly computation intensive and does not differentiate between the various physical properties of the fabrics like fiber denier, the polymer fiber, and weave pattern. This paper introduces a new modeling technique that uses artificial neural networks. Experimental permeability data for fabrics under biaxial strain conditions were obtained through a blister-inflation technique and were used to train the proposed network architecture. In this training environment, various properties of the fabric can be incorporated and the network can be trained to generalize relative to the environment. Once trained, the cause–effect pattern is assimilated by the network with approprate weights to produce a desired output. Fabrics tested in this study included nylon 66 fabrics with three different fabric deniers: 420, 630, & 840 and two types of weave, and two 650-denier polyster fabrics having different calendering effects. The predictions obtained from this neural network model agreed very well with the experimental data. This indicates that neural nets can be considered as a serious design tool use in determining permeability and biaxial stress–strain relationships for textile fabrics used in airbags.

ELECTRODE-ASSISTED SOIL WASHING

Contaminants in soils containing a high percentage of silt- and clay-sized particles typically are strongly adsorbed and very difficult to remove. However, a newly patented Electrode Assisted Soil Washing (EASW) process appears to be effective in removing petroleum hydrocarbons (gasoline, diesel, crude oil, etc.), chlorinated hydrocarbons, and heavy metals [7] from contaminated soils made up of a high percentage of clay and silt. The EASW process produces a washed soil material that meets site-specific regulatory requirements which allow the washed soil to be returned to the site without further treatment. Furthermore, the contaminated water generated by the process can be treated with standard biological methods. The EASW process can be used alone, or it can be used in combination with other soil-washing methods. In the latter case, the EASW process is particularly effective in the treatment of contaminated fines streams generated by other soil-washing techniques. The results of bench-scale batch tests with EASW used for washing petroleum hydrocarbons and pentachlorophenol contaminated soils will be discussed in this paper. Contaminant removal efficiencies of the EASW process, based on the difference between the contaminant concentrations in the feed soil and the washed soil, were above 99%. The performance of the EASW process in removing pentachlorophenol from soil was benchmarked against a commercially available process and found to be competitive.

Analysis of Fabrics used in Passive Restraint Systems – Airbags

This paper concerns the permeability and biaxial stress–strain behavior of woven fabrics used in the construction of automotive airbags. During deployment, gases are generated which inflate the airbag, distend it, and then energy is dissipated by the viscous flow of air forced to pass through the fabric. In order to quantify this latter behavior, the permeability of samples of expansible fabric was correlated with biaxial stress–strain behavior using a ‘blister-inflation’ technique. This paper presents the laboratory data obtained from two different commercial fabrics, nylon 66 and polyester, offered for use in the manufacture of automobile airbags. Overall, permeability measurements were made on the fabric samples for 15 different isobaric pressure drops (3.44 kPa to 103.42 kPa) and five different temperatures ranging from 8°C to 95°C. Both temperature and pressure were found to affect the permeability of the fabrics. For both types of fabrics tested, the maximum permeability was observed to coincide wit...

A realistic comparison of biaxial performance of nylon 6,6 and nylon 6 fabrics used in passive restraints—airbags

Nylon has been the material of choice for airbag construction because of its specific strength and dimensional stability during deployment. Of the nylons, nylon 6,6 has been widely used in airbag construction. In this article, we attempted to compare the performance of several commercial nylon 6,6 and nylon 6 fabrics offered, for use, to the auto industry. The performance of four traditional nylon 6,6 fabrics are compared with identical fabrics made from nylon 6 fibers. We used a test procedure championed by Chrysler but was developed in our laboratory called the blister-inflation. This test mimics the biaxial deformation of airbag fabric in a manner similar to the deformation of airbag fabric during actual deployment. Several other engineering properties of interest in airbag application are also addressed in this article for comparison purposes.

COMPARISON OF CONTRIBUTIONS TO ENERGY DISSIPATION PRODUCED WITH SAFETY AIRBAGS

In this paper a unique blister-inflation technique is described. This technique was used to evaluate the fabric properties necessary for energy dissipation. The performance of fabrics woven from two traditional commercial polymeric fibers offered for airbag construction were examined: (1) a traditional polyamide nylon 66; and (2) a high strenth poly(ethylene terephthalate). These two fabrics, with differences in fiber denier and weave, were evaluated for five different inflation temperature levels and at eleven different pressure drops. A kinetic-energy model was developed to account for the energy that should be dissipated by four different mechanisms. The paper focuses on and compares airbags made from the polymeric fibers which contain no vents. Based on the proposed model predictions, existing airbags appear to be adequate in their ability to dissipate energy over a rather short time frame. For the covering abstract of the conference see IRRD 875833.

Effects of moisture on structural silicone rubber sealants used in window glazing applications

When a structural sealant is exposed to moisture, a number of phenomena are known to occur which may cause it to deteriorate. The degree of deterioration, however, is a function of various parameters such as the type of sealant, the time of curing, etc. Silicone sealants are widely used for structural glazing applications because of their good resistance to weathering. In this study, moisture effects on commercial silicone sealants were monitored by observing changes in their physical properties. The moisture was applied as a water spray in which the pH of the water ranged from 3 to 11. The extremes of the pH range represent recorded values for acid rain (pH of 3) and basic cleaning solutions (pH of 11). Laboratory evaluations of deterioration were based on changes in tensile tangential modulus, percentage elongation and ultimate tensile stress.

Modeling of Crosslinking Mechanism When Structural Silicone Sealants Are Subjected to Moisture

Abstract Most polymeric sealants used in structural applications are organic and so some changes in the materials occur with passage of time: the material ages. The structural sealants function as a weather seal and when used with glazing also act as a binding agent for the glass to the substrate. As a weather seal, the sealants will be exposed to a wide variety of service conditions which include moisture. A question arises, therefore, as to the damage caused by moisture. When a structural sealant is exposed to moisture, a number of distinct phenomena are known to occur which can contribute to deterioration in the performance of the seal. In this study the moisture effect on the structural silicone sealant was correlated through crosslinking changes. A typical weathering event consisted of exposing the test coupons to moisture with pH levels ranging from 3 to 11, followed by drying. The extremes of the pH levels simulated acid rain (pH = 3) and cleaning solutions (pH = 11). Experimental data suggest that...