PVP2008-61243 UNIQUE METHOD FOR GENERATING DESIGN EARTHQUAKE TIME HISTORIES

ABSTRACT A method has been developed which takes a seed earthquake time history and modifies it to produce given design response spectra. It is a multi-step process with an initial scaling step and then multiple refinement steps. It is unique in the fact that both the acceleration and displacement response spectra are considered when performing the fit (which primarily improves the low frequency acceleration response spectrum accuracy). Additionally, no matrix inversion is needed. The features include encouraging the code acceleration, velocity, and displacement ratios and attempting to fit the pseudo velocity response spectrum. Also, "smoothing" is done to transition the modified time history to the seed time history at its start and end. This is done in the time history regions below a cumulative energy of 5% and above a cumulative energy of 95%. Finally, the modified acceleration, velocity, and displacement time histories are adjusted to start and end with an amplitude of zero (using Fourier transform techniques for integration). INTRODUCTION Time history analysis is an important technique for structural seismic analysis especially when the evaluated structural response is nonlinear. To perform such an analysis, a representative earthquake time history (or seed time history) is established for a structure being evaluated. To ensure that the variability in the response is addressed, a design response spectrum is then established using code guidance (e.g. ASCE 4-98 [1]). Because the design response spectrum does not match the response of the seed time history, the seed time history cannot be used for design evaluation. Instead, a modified time history must be used that is based on the seed time history, but provides a response defined by the design response spectrum. The method described in this paper is a way to modify the seed time history in such a way that it produces the design response

PVP2008-61244 UNIQUE METHOD FOR GENERATING DESIGN EARTHQUAKE TIME HISTORY SEEDS

ABSTRACT A method has been developed which takes a single seed earthquake time history and produces multiple similar seed earthquake time histories. These new time histories possess important frequency and cumulative energy attributes of the original while having a correlation less than 30% (per the ASCE/SEI 43-05 Section 2.4 [1]). They are produced by taking the fast Fourier transform of the original seed. The averaged amplitudes are then pared with random phase angles and the inverse fast Fourier transform is taken to produce a new time history. The average amplitude through time is then adjusted to encourage a similar cumulative energy curve. Next, the displacement is modified to approximate the original curve using Fourier techniques. Finally, the correlation is checked to ensure it is less than 30%. This process does not guarantee that the correlation will be less than 30% for all of a given set of new curves. It does provide a simple tool where a few additional iterations of the process should produce a set of seed earthquake time histories meeting the correlation criteria. INTRODUCTION Time history analysis is an important technique for structural seismic analysis especially when the evaluated structural response is nonlinear. To perform such an analysis, a representative earthquake acceleration time history (or seed acceleration time history) is established for a structure being evaluated. Manipulations of the seed are then performed to create a modified acceleration time history (or design acceleration time history) that produces a design acceleration response (per the ASCE/SEI 43-05 Section 2.4 [1]). This design acceleration time history can then be used for seismic analysis. Depending on the type of seismic analysis being performed, several design acceleration time histories may be required. The method described in this paper is a way t

Dickey-Lincoln School Lakes Project Environmental Impact Statement: Appendix F: Terrestrial Ecosystem Analysis (Supplement 2)

The overall study area encompassed the St. John River and its major tributaries; including the Little and Big Black Rivers (and their tributaries); and all lands extending 3.2 km (2 mi) beyond the maximum elevation of thv predicted impoundment of the Dickey Dam (1,560 km ). Research was concentra-ted in a portion of this area roughly bounded on the north by Chimenticook Stream, on the east by the St. John River, on the west by the United States-Canadian border, and on the south by a line drawn east-west through Seven Islands (Figure 1.0-1). Intensive marten studies were restricted to townships T14 R15 and T14 R16. Some radio-collared animals did not respect these boundaries and consequently were tracked in large portions of northern Maine and eastern Quebec

A History of American Settlement at Camp Atterbury

This report details the history of 19th and 20th century farm and community settlement within the Camp Atterbury Joint Maneuver Training Center, IN. It also provides a historic context for the identification, evaluation, and preservation of significant historic properties within installation boundaries. This historic context defines property types, poses research questions, and provides evaluation criteria based on the Camp Atterbury Joint Maneuver Training Center\u27s settlement history, in an effort to develop a comprehensive program of multiple site evaluation

Casting Yield Survey)

Abstract The results of a casting yield survey of steel foundries taken in the first quarter of 1997 are presented. Data collected in the survey includes the average, best case, and worst case castings yields for steel castings, and statistical data on the factors which influence casting yield. The average casting yield was found to be 53.3%, and the average best and worst case casting yields were found to be 72.7% and 33.2% respectively, based on a per response average. The response rate for this survey was 40% of the North American steel foundries contacted. Production, end-use, steel type, geometry, and risering methodology factors were identified and ranked in importance affecting casting yield. The following were statistically identified as important positive factors on casting yield, where yield increases with their increase: tons produced per pattern, amount of railroad and wear resistant end-use production, average section thickness, and use of risering rules developed in-house. A negative impact on yield was found to be related to pump and valve enduse production, and corrosion resistant steel production. The quantitative contributions of these factors on casting yield are presented. Unconventional yield improvements were rated very low relative to methods currently in use. Induction heating, compressed air cooling and stacking of castings were indicated as unconventional methods which had been attempted in foundries. Hardin, R.A., and Beckermann, C., "The Current State of Casting Yield: Results from the 1997 SFSA Yield Survey," in Proceedings of the 51 st SFSA Technical and Operating Conference, Paper No. 3.5, Steel Founders' Society of America, Chicago, IL, 1997. lNTRODUCTlON It is commonly believed that the average metal yield in the steel casting industry is approximately 50 to 55 percent. A primary goal of conducting the casting yield survey is to determine the yield with statistical accuracy for steel casting foundries. Regardless of the precise average yield, it can be safely assumed that most foundries must melt about twice as much steel as will be shipped as finished products. The resulting negative consequences of lower casting yield include additional costs in remelting scrapped steel (estimated to account for 7% of the total casting cost), the need for increased capacities for melt furnaces and melt handling, and increased costs associated with additional labor, molding and sand use. Increasing casting yield is therefore a major research priority for the Steel Founders' Society of America (SFSA). As part of that research plan, the SFSA is currently supporting a research project to achieve increased casting yield through new directional solidification techniques. The present casting yield survey was developed and conducted with the goals that it would assess the current yield performance among SFSA member companies, provide quantitative data on the casting process variables which affect yield (and to what extent), and poll the membership on promising yield improvement methods. From operational experience, it is understood that casting yield depends on factors such as type of casting (i.e. size, shape complexity, weight, and section thickness), alloys used, molding media and methods, and foundry practice (i.e. risering methods). The survey was designed to produce quantitative data on the relative importance of these factors. Finally, to further support the ongoing research project, it is hoped that the survey results will help identify types of castings and foundry practices as good candidates for application of the yield improvement techniques being developed as part of the project. Important objectives for the survey are summarized below: Obtain quantitative data on the current level of casting yield in steel foundries. Obtain data on the current methods of risering and yield improvement used. Acquire input from steel foundries on best yield improvement methods to pursue and important issues to consider in research. Use acquired data to correlate casting yield with casting variables. Use survey results in identifying and prioritizing yield improvement techniques. SURVEY DESCRIPTION The survey questionnaire was developed with input from the SFSA and SFSA member foundries. The result was a compact survey considering the amount of information collected. Following its development and approval, the survey was mailed from the SFSA to a pool of 93 foundries located in the U.S. and Canada. The response rate for the survey was 40%. The survey was divided into four sections; a general information section for contact data, and three sections of questions. The three question sections include general foundry characterization questions (section II with questions 1 through 9), current yield information questions (section Ill with questions 10 through 13), and questions regarding yield improvement methods (section IV with questions 14 through 18). The general foundry characterization questions covered information on tonnage, number of units of production, molding methods, typical casting geometry, and type of steels cast. For geometry data, participants were asked to give the minimum, maximum and average section thicknesses and the maximum dimensions for their typical castings' length, width, and height for a typical casting they produce. Annual energy usage for melting, and melting practice by weight percent of tonnage was also requested. Participants were directly asked for their average casting yield, which can be checked with the computed yield in the previous section for answer consistency. They were also asked to provide their highest possible yield on a "best case" casting and their worst yield on a "worst case" casting. The questions in the 2 final section were developed to collect data on issues dealing with yield improvement; identifying obstacles and looking for solutions. Causes of lowered casting yield and defects which limit yield were rated for importance, and conventional and unconventional methods of increasing casting yield were rated for effectiveness. Data in the SFSA Directory of Steel Founders and Buyers Guide was used to collect the foundries' end-use as percentage of their tonnage. RESULTS FOR THE SURVEY OF STEEL CASTING YlELD Data from the survey was entered into an Excel spreadsheet "database", and selected data from the spreadsheet was analyzed using the SAS statistical. The SAS program was used to produce the linear regression, ANOVA analysis (single and multivariate). Results from the survey's general foundry characterization section (section II) were also compared with results from two previous studies undertaken by the SFSA, the 1995 Capacity Study and the 1995 End-Use Survey, to confirm that the pool of respondents is representative of the industry. Extensive detail of the survey results is given in the survey report submitted to the SFSA (Steel Founders' Society of America 1997 Casting Yield Survey). Survey Production Data and Sample Pool Comparisons Data for the respondents' yearly production in tonnage and units produced per casting weight class are summarized in The percentage of tonnage produced by steel type and molding method is presented Product end-use data collected from the survey responses in combination with data in the SFSA Directory was used to produce the data given in A summary of averages and standard deviations from the section I survey data discussed above is given in Casting Geometry Data The reported minimum, maximum and average section thickness data (in inches) for a typical casting are plotted in Energy Use, Melting and Pouring The survey respondents' melting practice as a percentage of total was compared with the melt practice data reported in the 1995 SFSA Capacity Study. This showed the yield survey sample to be somewhat more highly skewed to the electric arc melting. The average reported energy (kW-hr) used per ton of metal melted was found to be 592 kW-hr per ton, and from the reported tonnage of castings shipped, the energy used per ton of metal shipped was found to be 1219 kW-hr per ton shipped. The average energy usage per ton of castings shipped is remarkably close to the value of 1300 kW-hr/ton as reported by McNaughton (1977), and is about 6% less. Also, there was a statistically significant relationship (found by ANOVA testing at the 0.15 level) between decreasing power usage per ton for foundries with increasing total tonnage; this data and its linear regression are shown in Responses to Yield Improvement Questions In the yield improvement section of the survey, respondents were asked to evaluate reasons for lower yield, relative importance of various defects to casting yield and various conventional and unconventional yield improvement techniques. In The evaluation of conventional and unconventional yield improvement techniques are presented in Tables VII and VIII. This feedback identified worthwhile yield improvement methods. Respondents were also 5 asked to indicate whether or not their foundry had used a given technique. For unconventional yield improvement methods, only induction heating of risers, compressed air chilling, and stacking were indicated as having been used by 1, 2, and 6 foundries respectively. The conventional improvement method evaluations are given in The ratings for unconventional yield improvement methods are presented in 6 Casting Yield Data The reported (average yield as reported directly in the survey) and computed (from the tonnage shipped and melted) casting yields averaged per survey response were 53.3% and 52.1%, respectively. They are remarkably close, as they should be. This serves as a check on this critical figure reported in the survey. The distribution of the reported average yield is given in When yields are computed on the basis of steel tonnage produced by risering method as shown in 7 Casting simulation is one of the lower resulting yields. This could be explained by the fact that casting simulation is generally used on the toughest parts a foundry casts, and the foundries which use it are casting difficult and complex parts. Hence, the comparison is not fair. Here, again, note that a high average yield appears to go hand-in-hand with a high minimum yield while the maximum yield appears to have little effect on the average yield. The average, maximum, and minimum casting yields averaged on a per tonnage produced by steel type, by molding method and for a given end use are also given in For steel type Carbon and wear resistant steel show the highest average casting yields, and carbon in particular shows the highest worst case (minimum) yield. Heat resistant steel shows the highest maximum yield on average. Corrosion resistant steels show the lowest average casting yield, which is also indicated by its very low value of worst case yield. The maximum casting yield values vary by about 10% while the minimum (or worst case) casting yield show a 21% variation. 9 For molding type There is the least degree of variation between yields when averaged by tonnage produced by molding method. However, green sand casting molding tonnage produces on average a noticeably higher yield. It should be noted that, green sand casting shows a high correspondence with railroad end-use. For casting end-use A dramatically higher casting yield is observed in railroad producers. As observed in The next highest yields appear in the mining and truck producing categories. These categories also revealed to have the next highest minimum observed yields. This is more evidence that higher average yield is achieved by increasing the yield of worst case castings (rather than getting the best possible yield out of best case castings). The lowest average and worst case (minimum) casting yields were noted in the pump and valve categories, and the oil, military, construction and industrial categories were not much better. The military production best case (or maximum) observed yield is the lowest of any category. This may not be too surprising owing to the standards which are required. In ANALYSIS OF FACTORS INFLUENCING CASTING YIELD In the yield survey results of the previous section the relative importance and interactions between factors affecting casting yield were not statistically prioritized or identified. By using the analysis of variance (ANOVA) and multivariate ANOVA analysis technique, the data gathered in the survey regarding casting geometry and production data are added to the analysis to search for the most important factors affecting casting yield. In ANOVA analysis, the possible sources of variation of a variable (say casting yield in our case) are tested for the significant factors contributing to its observed variation. If a factor or source of variation is found to be a statistically important contribution to that variation, the ANOVA analysis produces two figures of merit which signify the factor's importance. One of these, the F-ratio (or Fisher ratio) is a measure of the statistical significance of a factor; the higher the F-ratio is, the greater the probability that a given factor has a significant effect on the variation of casting yield. The second figure, the significance (or p-value), is an indicator of how random the effect of a given factor is on the variation in the variable of interest. A high significance indicates a high probability that a factor has a random effect, and the lower the significance the greater the probability that the factor's effect is not random. The ANOVA analysis also provides the contribution to the variation in the variable of interest due to a given factor. In this case, the ANOVA analysis gives the contribution in percentage of the variation in casting yield due to factor of interest. The ANOVA analysis is used here with linear regression to indicate the manner and degree to which the casting yield is effected by a given factor. Here the dependence of casting yield on a factor is prescribed to 10 be linear, and ANOVA analysis will be used to detect which of the hypothesized effects (or their interactions) are statistically significant. The results of the one-way ANOVA tests with no interactions on factors affecting average, minimum, and maximum casting yield are given in The effect of a variable's influence on increasing or decreasing yield can be determined by the regression formula given in the final column of each table. The linear regression formulas contain the SAS variables V1, V2, and V3 for average, maximum and minimum yield respectively. The independent variable is the variable being considered in that table row. Tables in the complete survey report also detail all variables considered which were found not to have a statistical effect on yield. For consistency the ANOVA table results given here were computed without discarding any observations. Results of ANOVA for Average Casting Yield Variables with the strongest statistical influence on average casting yield are summarized below (in order of significance): Factors of Strong Significance on Average Yield 1, Tonnage per pattern (yield increases with its increase) 2. Percentage of pump and valve production (yield decreases with its increase) 3. Percentage of rail production (yield increases with its increase) 4. Percentage use of in-house risering rules (yield increases with its increase) 5. Percentage of industrial production (yield decreases with its increase) 6. Percentage of corrosion resistant production (yield decreases with its increase) 7. Minimum section thickness (yield increases with its increase) Factors of Significance on Average Yield 8. Average section thickness (yield increases with its increase) 9. Percentage of wear resistant production (yield increases with its increase) 10. Typical casting "box" volume/average casting weight (yield decreases with its increase) The most significant factor influencing average casting yield is a variable related to mass production, tonnage per pattern. This variable does not distinguish between many casting made of a single smaller pattern, or fewer castings made of larger/heavier patterns. In both cases foundries are able to refine and optimize their process leading to higher yields. The number of units per pattern did show a weak statistical significance when all observations were included, and average casting weight (formed by the tonnage per pattern divided by the number of units per pattern) showed no statistical influence on casting yield. However, when one influential observation was discarded, the number of units per pattern was found to be significant 11 12 with p = 0.0011, and was associated with a positive effect on yield with its increase. It was already shown in Since corrosion resistant steel production showed a strong statistical association with both pump and valve production (p-value = 0.0015), it remains to be determined whether this is due to the type of steel itself or a dependence on the end use of many corrosion resistant steel castings. An analysis using induction melting showed a strong statistical correlation with corrosion resistant steel (p-value = 0.0010) and weak association with pumps and valves (p-value = 0.0506), and was shown to have no effect on yield. This is evidence that the deleterious effect of corrosion resistant steels is due to their association with pump and valve castings rather than the inherent properties of corrosion resistant steel. However, the results of Varga et al. (1958) among others show clearly the additional difficulties involved with feeding castings of increasing alloying elements. On their face the survey results directly support the poor casting yield/feeding characteristics of corrosion resistant steels. Two thickness variables appear next in the list; minimum thickness which has a strong significance with average yield and average section thickness which has an effect, but in the statistical class below "strong". Note that minimum thickness appears to be more important than the average thickness, and that these geometric variables, though identified as important, are less important than "production" related variables. Maximum thickness was not identified as a significant effect on average casting yield. Following percentage of wear resistance production in the list, is a variable derived from responses to geometric questions as to casting size and weight. By taking the reported typical casting's length, width and height and then multiplying them to create a casting "box" volume, and then dividing this volume by the foundry's average casting weight, a specific volume for the casting's rangyness was formed. For castings whose dimensions were large, but the average weight was small; this factor has a large value, and it is assumed that such a casting is rangier than a casting whose overall box dimensions are smaller and whose weight is higher. It was found that this derived variable proved a statistically significant factor, and that its effect is as one would logically expect, when its value increases (i.e. a rangier casting) it is associated with a slight decrease in average casting yield. It is also important to note the factors which do not have an influence on casting yield, according to the survey responses. Average casting weight had no influence, and only a weak influence was observed with the number of different casting patterns produced each year. Molding practice had no discernable effect. In the risering rules category, only "in-house rules" was found to have an important influence and it was positive. All other risering methodologies either had "no effect" or "not much", and when the effect was found it was negative (for SFSA Guidelines, in-house rules based software and casting simulation). Variables which might be expected not to have an effect on yield by themselves such as casting length, width and height, and melting practice; did not. Minimum and maximum casting yield data were also analyzed for factors influencing them. Unlike average yield and minimum yield few statistically defendable factors influencing maximum casting yield were found. The dependence between the three reported yields were also examined, and the only dependence found was between average and minimum reported casting yields. As shown in Results of ANOVA for Minimum Casting Yield A number of the factors which were found to have a strong influence on average yield appeared as strong factors on minimum casting yield. The factors influencing minimum casting yield are listed below in order of significance: Factors of Strong Significance on Minimum Yield 1. Tonnage per pattern (yield increases with its increase) 2. Minimum section thickness (yield increases with its increase) 3. Percentage of rail production (yield increases with its increase) 4. Percentage of pump and valve production (yield decreases with its increase) 5. Number of units per pattern (yield increases with its increase) Factors of Significance on Minimum Yield 6. Percentage use of in-house risering rules (yield increases with its increase) 7. Percentage of oil end-use production (yield decreases with its increase) 8. Percentage of industrial end-use production (yield decreases with its increase) 9. Typical casting "box" volume/average casting weight (yield decreases with its increase) As with average yield, variables dealing with mass production and production end-use appear to be the most important variables effecting minimum casting yield. The tonnage per pattern is the most important factor contributing to minimum casting yield accounting for 50% of the variatio

E. Sachs

Introduction 1.1 Motivation. Two needs which are key to industrial productivity and competitiveness are the reduction in time to market for new products and the flexible manufacture of products in small quantities. This work targets a critical subset of the problems that must be overcome in order to achieve shorter product development cycles and flexible manufacturing for mechanical parts. The problems addressed are rapid prototyping, rapid fabrication of tooling, and the low cost manufacture of tooling. A major contributor to the time to market for new products is the time required to fabricate prototypes. Rapid prototyping can shorten the product development cycle and improve the design process by providing rapid and effective feedback to the designer. Some applications require rapid prototyping of nonfunctional parts for use in assessing the aesthetic aspect of a design or the fit and assembly of a design. Other applications require functional parts. Often, it is advantageous if the functional part is fabricated by the same process that will be used in production. A second major contributor to the time to market is the time required to develop tooling, such as molds and dies. For some types of tooling, such as injection molding dies, the turnaround time for the design and fabrication of a tool routinely extends to several months. The long lead times are due to the fact that tooling is generally one of a kind and can be extremely complex, requiring a great deal of human attention to detail

Magnetic confinement of an electric arc in transverse supersonic flow

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/77344/1/AIAA-2803-657.pd

A systematic review, evidence synthesis and meta-analysis of quantitative and qualitative studies evaluating the clinical effectiveness, the cost-effectiveness, safety and acceptability of interventions to prevent postnatal depression

Background: Postnatal depression (PND) is a major depressive disorder in the year following childbirth, which impacts on women, their infants and their families. A range of interventions has been developed to prevent PND. Objectives: To (1) evaluate the clinical effectiveness, cost-effectiveness, acceptability and safety of antenatal and postnatal interventions for pregnant and postnatal women to prevent PND; (2) apply rigorous methods of systematic reviewing of quantitative and qualitative studies, evidence synthesis and decision-analytic modelling to evaluate the preventive impact on women, their infants and their families; and (3) estimate cost-effectiveness. Data sources: We searched MEDLINE, EMBASE, Science Citation Index and other databases (from inception to July 2013) in December 2012, and we were updated by electronic alerts until July 2013. Review methods: Two reviewers independently screened titles and abstracts with consensus agreement. We undertook quality assessment. All universal, selective and indicated preventive interventions for pregnant women and women in the first 6 postnatal weeks were included. All outcomes were included, focusing on the Edinburgh Postnatal Depression Scale (EPDS), diagnostic instruments and infant outcomes. The quantitative evidence was synthesised using network meta-analyses (NMAs). A mathematical model was constructed to explore the cost-effectiveness of interventions contained within the NMA for EPDS values. Results: From 3072 records identified, 122 papers (86 trials) were included in the quantitative review. From 2152 records, 56 papers (44 studies) were included in the qualitative review. The results were inconclusive. The most beneficial interventions appeared to be midwifery redesigned postnatal care [as shown by the mean 12-month EPDS score difference of –1.43 (95% credible interval –4.00 to 1.36)], person-centred approach (PCA)-based and cognitive–behavioural therapy (CBT)-based intervention (universal), interpersonal psychotherapy (IPT)-based intervention and education on preparing for parenting (selective), promoting parent–infant interaction, peer support, IPT-based intervention and PCA-based and CBT-based intervention (indicated). Women valued seeing the same health worker, the involvement of partners and access to several visits from a midwife or health visitor trained in person-centred or cognitive–behavioural approaches. The most cost-effective interventions were estimated to be midwifery redesigned postnatal care (universal), PCA-based intervention (indicated) and IPT-based intervention in the sensitivity analysis (indicated), although there was considerable uncertainty. Expected value of partial perfect information (EVPPI) for efficacy data was in excess of £150M for each population. Given the EVPPI values, future trials assessing the relative efficacies of promising interventions appears to represent value for money. Limitations: In the NMAs, some trials were omitted because they could not be connected to the main network of evidence or did not provide EPDS scores. This may have introduced reporting or selection bias. No adjustment was made for the lack of quality of some trials. Although we appraised a very large number of studies, much of the evidence was inconclusive. Conclusions: Interventions warrant replication within randomised controlled trials (RCTs). Several interventions appear to be cost-effective relative to usual care, but this is subject to considerable uncertainty. Future work recommendations: Several interventions appear to be cost-effective relative to usual care, but this is subject to considerable uncertainty. Future research conducting RCTs to establish which interventions are most clinically effective and cost-effective should be considered