No description available.

ABSTRACT Water and Air Quality Performance of a Reciprocating Biofilter Treating Dairy Wastewater Seppi Matthew Henneman Agricultural non-point source pollution is the leading water quality problem in surface water and the second leading problem in ground water in the US. Among the contaminants, nutrients (such as nitrogen, phosphorus, potassium) can be transported from agricultural fields when cropland is not managed properly. In California, dairy manure application to cropland has become tightly regulated with the goal of decreasing such nutrient pollution. Dairies unable to balance their manure nutrient supply with cropland application area may benefit from a nitrogen removal technology. One such technology is the reciprocating biofilter, known as the ReCip® technology. A pilot-scale ReCip® unit was installed at the Cal Poly dairy to evaluate its treatment efficacy, in particular for nitrogen removal, when treating wastewater from flush dairies. This pilot-scale system was the first application of the ReCip® technology to dairy wastewater, and recently it was found to be effective for removal of ammonium, total nitrogen, and biochemical oxygen demand (BOD). In the ReCip®, wastewater is repeatedly pumped back and forth between two gravel-filled basins. This reciprocation creates two treatment environments: an aerobic environment, which promotes reactions such as nitrification and BOD oxidation, and an anoxic/anaerobic environment, which promotes reactions such as denitrification of nitrate into nitrogen gas and methanogenesis. At Cal Poly, the ReCip® treated storage lagoon water, and ReCip® effluent containing nitrate was returned to the lagoon, possibly contributing to odor control. Emission of air pollutants is a concern about dairy waste in general (volatile organic compounds, hydrogen sulfide, methane, etc.) and for nitrification-denitrification systems in particular (nitrous oxide). In the present work, the first detailed air emission study was conducted on ReCip®. Emissions of air pollutants were measured with flux chambers during different seasons, and, simultaneously, the water quality within the pore volume of the gravel beds was measured to explore whether pore water quality correlated to air emissions. These air emissions studies were performed within a yearlong study of overall ReCip® treatment performance. Water quality constituents measured were pH, alkalinity, temperature, dissolved oxygen (DO), total ammonia nitrogen (TAN), soluble nitrogen, soluble non-purgeable organic carbon, nitrite, and nitrate. During the submerged phase of the reciprocation cycle, pore water DO generally declined from 1-2 mg/L to <0.1 mg/L, while TAN declined and nitrate accumulated, although total nitrogen also declined due to denitrification. The extent of denitrification was correlated to influent BOD loading. The average removals by the ReCip® were 93% TAN, 61% CBOD5, 74% TKN, and 57% TSS. A simple CBOD5 removal model was developed that described and predicted CBOD5 ­removal in the system. Key air pollutants emitted by the ReCip® and their annual mean concentrations were nitrous oxide (0.74 ppm), ammonia (0.15 ppm), and methane (3.85 ppm). The air emission potential of the lagoon water influent was compared to that of the ReCip® effluent. The decreases in emission potential were 82% for ammonia, 93% for methane, and 99% for hydrogen sulfide. The average masses emitted (g emitted/kg loaded into system) by the ReCip® were 1.7 g N2O/kg N, 0.15 g NH3/kg N, 2.1 g CH4/kg CBOD5, 1.0 g ethanol/kg CBOD5,and 0.004 g H2S/kg CBOD5.

It is projected that by 2026, most workloads in cloud data centers will be Deep Learning (DL) workloads. However, these workloads pose significant challenges due to their high computational demands, requiring infrastructure and platform advancements to meet DL’s performance, efficiency, and scalability requirements. One emerging problem in large-scale DL is the data stall issue, which occurs when DL models require extensive input data pre-processing, causing CPUs to struggle to keep up with the data consumption demands of GPUs during the training stage. This results in the DL pipeline stalling and GPUs running idle. Our work aims to fundamentally address the data stall issue in modern pre-processing DL pipelines. Traditional solutions involve allocating more CPUs to the pre-processing stage to meet GPU demands, but this approach significantly increases energy con- sumption and provisioning costs. For example, Meta recently disclosed that their DLRM pipeline requires 9 to 55 CPU servers per trainer node, depending on the workload. Our research explores offloading common pre-processing primi- tives to programmable network hardware, specifically Tofino2-equipped switches known for their high bandwidth and energy efficiency, and the Bluefield-2 Smart- NIC. Our initial power measurements demonstrate that Tofino2 and Bluefield-2 achieve 11.6x and 3.0x higher throughput per Watt, respectively, compared to a generic x86 or AMD CPU while performing pre-processing operations. However, due to Tofino2’s limitations in terms of the operations it can perform compared to a CPU, several design optimizations are required to fully exploit the potential of programmable network devices.

Kvarnängens Häst- och samtalscenter präglas av en öppen natur med lummig skog. Platsen för projektet är utvald eftersom den sammanfaller med ungdomars troliga rörelsemönster i området då den ligger nära kommunens enda gymnasium samt flertalet sportanläggningar. Stillasittande hos barn och unga har i flera studier visat sig försämra den psykiska ohälsan. Därför har jag skapat detta centret; för att ge målgruppen en möjlighet till både samtal och möten. Hästar som terapi har visat sig gynnsam då det gäller ungdomars psykiska hälsa. Det understryks av den kognitiva beteendeterapin som menar att vårt beteende samspelar med vår närmiljö. I terapin arbetar man med att stärka ansvarstagande, självförtroende och självkänsla samt att minska depression, ångest och beteendeproblem.  Projektets konstruktion är av gran, med ett bärande pelarsystem. Det inbyggda fackverket döljs av ett rundat innertak och den inre konstruktionen präglas av takets runda form samt av takfönster  som släpper in och filtrerar dagens ljus.  Den yttre fasaden är behandlad med ”Shou Sugi Ban”; en japansk teknik och tradition där träytan bränns/förkolnas. Tekniken grundar sig i filosofin “Wabi-Sabi”, där förändring ses som vacker och där skavankerna får ta plats; lagningen ses som positiv, och som en naturlig del av livet. / The open forestry environment surrounding Kvarnängen Horse- and youth center with its proximity to schools and sports facilities was chosen specifically for this project. In later years children and young adults have been moving towards a more sedentary lifestyle, and because of this, some believe that there has been an increase of mental illnesses. Due to this I have chosen to center my project around  this issue. Horses and riding as a form of therapy has long shown to be beneficial. Cognitive behavioral therapy is the idea that the way we act coexists with our environment; combining the two aims to strengthen the ability to take ownership, self confidence and self-esteem, but also decrease depression, anxiety and behavioral issues. The construction of the project is of pine, with columns and hidden lattice trusses concealed with a rounded interior ceiling. The rounded ceiling and skylights filter and reflect the lights and colors of the day.  The outside panel has been burned and charred with a Japanese technique “Shou Sugi Ban”. The philosophy of the technique is called “Wabi-Sabi”; where faults are seen as beautiful and the mending process as positive and  as a part of life.

No description available.

No description available.

No description available.

No description available.

This dissertation aims to present detailed analysis of the small scale wind energy conversion system (WECS) design and implementation. The dissertation will focus on implementing a hardware prototype to be used for testing different control strategies applied to small scale WECSs. Novel control algorithms will be proposed to the WECS and will be verified experimentally in details. The wind turbine aerodynamics are presented and mathematical modeling is derived which is used then to build wind simulator using motor generator (MG) set. The motor is torque controlled based on the turbine mathematical model and the generator is controlled using the power electronic conversion circuits. The power converter consists of a three phase diode bridge followed by a boost converter. The small signal modeling for the motor, generator, and power converter are presented in details to help building the needed controllers. The main objectives of the small scale WECS controller are discussed. This dissertation focuses on two main regions of wind turbine operation: the maximum power point tracking (MPPT) region operation and the stall region operation. In this dissertation, the concept of MPPT is investigated, and a review of the most common MPPT algorithms is presented. The advantages and disadvantaged of each method will be clearly outlined. The practical implementation limitation will be also considered. Then, a MPPT algorithm for small scale wind energy conversion systems will be proposed to solve the common drawback of the conventional methods. The proposed algorithm uses the dc current as the perturbing variable and the dc link voltage is considered as a degree of freedom that will be utilized to enhance the performance of the proposed algorithm. The algorithm detects sudden wind speed changes indirectly through the dc link voltage slope. The voltage slope is also used to enhance the tracking speed of the algorithm and to prevent the generator from stalling under rapid wind speed slow down conditions. The proposed method uses two modes of operation: A perturb and observe (PandO) mode with adaptive step size under slow wind speed fluctuation conditions, and a prediction mode employed under fast wind speed change conditions. The dc link capacitor voltage slope reflects the acceleration information of the generator which is then used to predict the next step size and direction of the current command. The proposed algorithm shows enhanced stability and fast tracking capability under both high and low rate of change wind speed conditions and is verified using a 1.5-kW prototype hardware setup. This dissertation deals also with the WECS control design under over power and over speed conditions. The main job of the controller is to maintain MPPT while the wind speed is below rated value and to limit the electrical power and mechanical speed to be within the system ratings when the wind speed is above the rated value. The concept of stall region and stall control is introduced and a stability analysis for the overall system is derived and presented. Various stall region control techniques are investigated and a new stall controller is proposed and implemented. Two main stall control strategies are discussed in details and implemented: the constant power stall control and the constant speed stall control. The WECS is expected to work optimally under different wind speed conditions. The system should be designed to handle both MPPT control and stall region control at the same time. Thus, the control transition between the two modes of operation is of vital interest. In this dissertation, the light will be shed on the control transition optimization and stabilization between different operating modes. All controllers under different wind speed conditions and the transition controller are designed to be blind to the system parameters pre knowledge and all are mechanical sensorless, which highlight the advantage and cost effectiveness of the proposed control strategy. The proposed control method is experimentally validated using the WECS prototype developed. Finally, the proposed control strategies in different regions of operation will be successfully applied to a battery charger application, where the constraints of the wind energy battery charger control system will be analyzed and a stable and robust control law will be proposed to deal with different operating scenarios. / Ph. D.

The work presented in this thesis attempts to provide an understanding of the physics behind the dynamic stall process by simulating the flow past pitching NACA-0012 airfoil at 100,000 and 1 million Reynolds number based on the chord length of the airfoil and at different reduced frequencies of 0.188 and 0.25 respectively in a three dimensional flow field. The mean angles of attack are 12 deg. and 15 deg. and the amplitudes of pitching are 6 deg. and 10 deg. respectively. The turbulence in the flow field is resolved using large eddy simulations with dynamic Smagorinsky model at the sub grid scale. The lift hysteresis plots of this simulation for both the configurations are compared with the corresponding experiments. The development of dynamic stall vortex, vortex shedding and reattachment as predicted by the present study are discussed in detail. There is a fairly good match between the predicted and experimentally measured lift coefficient during the upstroke for both cases. The net lift coefficient for the Re = 100,000 case during downstroke matches with the corresponding experimental data, the present study under-predicts the lift coefficient as compared to the experimental values at the start of downstroke and over-estimates for the remaining part of the downstroke. The trend of the lift coefficient hysteresis plot with the experimental data for the Re = 1 million case is also similar. This present simulations have shown that the downstroke phase of the pitching motion is strongly three dimensional and is highly complex, whereas the flow is practically two dimensional during the upstroke. / Master of Science