The spray drying process is widely established in the industry worldwide. However, due to its complexity in predicting variables, the technology is often regarded as a "Black box" process. In this study, a model based on energy and mass balances is designed and validated using Matlab/Simulink software and real data from a medium-sized machinery, specifically the Production Minor manufactured by GEA NIRO S/A. Additionally, the simulation incorporates a heat recovery system based on a heat pump, and its economic feasibility is examined.The simulation is validated for a narrow range of variables and demonstrates an accuracy of approximately 95% in most cases.The heat recovery system achieves an average natural gas savings of 0.43 kg/h. However, this saving is accompanied by an additional electrical consumption of 2.1 kW resulting from the operation of the heat pump.The economic feasibility study of the heat recovery system reveals an extra production cost of 0.1€/h in exchange for a 36% average reduction in natural gas dependency.

In a world with high energy cost, the efficiency of motors becomes increasingly important. Thereby, the understanding of loss mechanics is of great significance and having accurate simulation models for the efficiency of motors is crucial.    Bosch Rexroth Mellansel has developed a new radial piston hydraulic motor with high power, capable of operating at high torque and speed. In this master thesis the newly developed motor will be examined and undergo a lab test to determine its efficiency. The results from this will then be used to improve the current simulation model and aim for a physical model that align with the efficiency results. Furthermore, the loss mechanics of the motor is important and will be studied during this thesis. The loss mechanics in a motor can be split into two parts, hydro-mechanical and volumetric losses. Hydro-mechanical losses refer to the losses due to both friction and hydraulic flow. The losses in the fluid flow are in turn divided into two parts, the major losses and the minor losses which are the friction losses in the fluid and the losses due to geometric changes in the channels respectively. The volumetric losses are on the other hand the losses from internal and external leakage of the hydraulic fluid, and compression flow which is the extra flow that occurs when the fluid changes density.  In order to determine efficiency values from a radial piston hydraulic motor, a test specification was written containing the information needed to perform the test, including two different methods, the pressure and torque method, and the sensors needed to measure the different parameters. For the hydro-mechanical efficiency the uncertainty is 0.1% for the pressure method and 0.15% for the torque method. The test was performed for several different rotational speeds and different pressure points. An improved model was developed from the test results by testing and optimization, and it was found that having the losses due to geometric changes in the channels, depend on Reynolds number agreed better with the test result. However, the improved simulation model does not align as well with the test result for all measured points. Hence a further investigation on the friction model and the dependence on pressure might improve the model further. However, it was found that for a specific sub test, the new model had a mean difference from the pressure method test result of 10^-3. While the mean difference for the unaltered simulation model was 10^-2, hence the new simulation model is an improvement. Therefore, the outcome of this master thesis is an improved simulation model for the newly developed radial piston hydraulic motor QMp 560-560 but also for future motors to come.

No description available.

No description available.

Energy calculations are used for many purposes, for example during the design andconstruction phase to comply with Boverket’s building regulations, energy declarations or toachieve energy saving in a building. A main problem in the design process of a new building,is to accurately predict the energy performance. The energy calculations require data fromdifferent interacting components, which have been shown to be challenging to measure. Thisproblem arises in particularly for complex buildings, notably office buildings. Due to the lackof detailed energy models and analyses of the differences between the model and reality foroffice buildings in Sweden, this report aims to answer the question: What are the causes ofdeviations between the models and the measurements of energy usage and indoor airtemperature for the studied office building? The office building Sthlm New 04 was modeledas a whole-building within IDA ICE and the simulated data was compared with measureddata from 2021 that was provided by Skanska Fastigheter.During the design of the model, the simulation model was fed with external source files (withmeasured data) to make the model operate at the same time as the real system. Since therewas no logged occupancy data for this office building, it was assumed that occupancy wasdistributed equally in all office zones. The model has a detailed HVAC system to make themodel as accurate as possible.The result showed overall a good agreement with the measured data, especially for thesimulated district heating and cooling. However, a closer look revealed that there were somedifferences that the model did not account for. The building’s three Air-handling units alsoshowed a good agreement with an average of -0.3 °C, -0.2 °C and +0.2 °C. The resultshighlight several problems with modeling and measured data. Under the influence ofassumptions and hard to define input data, there may be misinterpretation by the modeler.Other reasons could be sensor errors or manufacturing errors by most of the errors could becorrected by a more detailed occupancy in the model. However, this study has shown thatthe detailed model can be used for a fair comparison between the simulated model and thereal building, although there may be some discrepancies. Undoubtedly, it is difficult to createa model that exactly matches the real building, but this model is a good representation thatcan be used for future research such as digital twin.

The complexity of software development projects makes estimation and management very difficult. There is a need for improved cost estimation methods and new models of lifecycle processes other than the common waterfall process. This work has developed a new simulation model of the spiral development lifecycle as well as an approach for using simulation for cost and schedule estimation. The goal is to provide a tool that can analyze the effects of a spiral development process as well as a tool that illustrates the difficulties management faces in forecasting budgets at the beginning of a project which may encourage more realistic approaches to budgetary planning. A new discrete event process model of the incremental spiral development lifecycle approach was developed in order to analyze the effects this development approach has on the estimation process as well as cost and schedule for a project. The input data for the key variables of size, productivity, and defect injection rates in the model was based on analysis of Software Engineering Laboratory data and provided for analysis of the effects of uncertainty in early project estimates. The benefits of combining a separate system dynamics model with a discrete event process models was demonstrated as was the effects of turnover on the cost and schedule for a project. This work includes a major case study of a cancelled NASA software development project that experienced cost and schedule problems throughout its history. Analysis was performed using stochastic simulation with derived probability distributions for key software development factors. A system dynamics model of human resource issues was also combined with the process model to more thoroughly analyze the effects of turnover on a project. This research has demonstrated the benefits of using a simulation model when estimating to allow for more realistic budget and schedule determination including an interval estimate to help focus on the uncertainty of early estimates.

Emerging memory technologies are being intensively investigated for extending Moore\'s law in the next decade. The conductive bridge random access memory (CBRAM) is one of the most promising candidates. CBRAM shows unique nanoionics-based filamentary switching mechanism. Compared to flash memory, the advantages of CBRAM include excellent scalability, low power consumption, high OFF-/ON-state resistance ratio, good endurance, and long retention. Besides the nonvolatile memory applications, resistive switching devices implement the function of memristor which is the fourth basic electrical component. This research presents the characterization and modeling of Cu/TaOx/Pt resistive switching devices. Both Cu and oxygen vacancy nanofilaments can conduct current according to the polarity of bias voltage. The volatile resistive switching phenomenon has been observed on Cu/TaOx/delta-Cu/Pt devices and explained by a flux balancing model. The resistive devices are also connected in series and in anti-parallel manner. These circuit elements are tested for chaotic neural circuit. The quantum conduction has been observed in the I-V characteristics of devices, evidencing the metallic contact between the nanofilament and electrodes. The model of filament radial growth has been developed to explain the transient I-V relation and multilevel switching in the metallic contact regime. The electroforming/SET and RESET processes have been simulated according to the mechanism of conductive filament formation and rupture and validated by experimental results. The Joule and Thomson heating effects have also been investigated for the RESET processes. / Ph. D.

No description available.

Recent U.S. legislation applies a precautionary approach to setting catch regulations in federal fisheries management. A transparent approach to complying with federal guidelines involves calculating the catch recommendation that corresponds to a specified probability, P*, of exceeding the "true" overfishing limit (OFL) located within an estimated distribution. The P* methodology aims to manage the risk of overfishing explicitly, but choice of P* alone does not provide sufficient information on all of the risks associated with a control rule—both the probability of overfishing and the severity of overfishing. Rather, the ramifications of P* choices depend on the amount of uncertainty in the stock assessment and on the life history of the species in question. To evaluate these effects on the risks associated with P* rules, my study simulated fishing three example species under three levels of uncertainty. Trends identified among example species were consistent with predictions from life history. Periodic strategists, which have highly variable recruitment, experienced probabilities of overfishing which exceeded P* and which increased in time. Equilibrium strategists showed more predictable risks of overfishing but may have less capacity to recover from depleted biomass levels. Differences in the size of the OFL distribution—representing differences in levels of uncertainty—led to mixed results depending on whether the distribution was biased or whether uncertainty was fully characterized. Lastly, because OFL distributions are themselves estimates and subject to uncertainty in their shape and size, lower P* values closer to the tails of the estimated distribution produced more variable resulting risks. / Master of Science

The U.S. pelagic longline fishery catches 98% of domestic swordfish landings but is also one of the three fisheries most affecting federally protected sea turtles (Crowder and Myers 2001, Witherington et al 2009). Bycatch by fisheries is considered the main anthropogenic threat to sea turtles (NRC 1990). Accurate and precise bycatch estimates are imperative for sea turtle conservation and appropriate fishery management. However, estimation is complicated by only 8% observer coverage of fishing and data that are hierarchical in structure (i.e., multiple sets per trip), zero-heavy (i.e., bycatch is rare), and often overdispersed (i.e., larger variance than expected). Therefore, I evaluated two predominant bycatch estimation methods, the delta-lognormal method and generalized linear models, and investigated improvements in uncertainty incorporation. I constructed a simulation model to evaluate bycatch estimation at two spatial scales under ten spatial models of sea turtle, fishing set, and observer distributions. Results indicated that distributing observers relative to fishing effort and using the delta-lognormal-strata method was most appropriate. The delta-lognormal-strata 95% confidence interval (CI) was wider than statistically appropriate. The delta-lognormal-all sets pooled 95% CI was narrower but simulated bycatch was above the CI too frequently. Thus, I developed a bycatch estimate risk distribution to incorporate uncertainty in bycatch estimates. It gives managers access to the entire distribution of bycatch estimates and their choice of any risk level. Results support the management agency's observer distribution and estimation method but suggest a new procedure to incorporate uncertainty. This study is also informative for many similar datasets. / Master of Science