274 research outputs found

    State Space Methods in Stata

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    We illustrate how to estimate parameters of linear state-space models using the Stata program sspace. We provide examples of how to use sspace to estimate the parameters of unobserved-component models, vector autoregressive moving-average models, and dynamic-factor models. We also show how to compute one-step, filtered, and smoothed estimates of the series and the states; dynamic forecasts and their confidence intervals; and residuals.

    State Space Methods in Stata

    Get PDF
    We illustrate how to estimate parameters of linear state-space models using the Stata program sspace. We provide examples of how to use sspace to estimate the parameters of unobserved-component models, vector autoregressive moving-average models, and dynamic-factor models. We also show how to compute one-step, filtered, and smoothed estimates of the series and the states; dynamic forecasts and their confidence intervals; and residuals

    Fourth-Generation Fan Assessment Numeration System (FANS) Design and Performance Specifications

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    The Fan Assessment Numeration System (FANS) is a measurement device for generating ventilation fan performance curves. Three different-sized FANS currently exist for assessing ventilation fans commonly used in poultry and livestock housing systems. All FANS consist of an array of anemometers inside an aluminum shroud that traverse the inlet or outlet of a ventilation fan. The FANS design has been updated several times since its inception and is currently in its fourth-generation (G4). The current design iteration (FANS-G4) is reported in this article with an emphasis on the hardware and software control, data acquisition systems, and operational reliability. Six FANS-G4 units were fabricated at the University of Kentucky (UK) Agricultural Machinery Research Laboratory and calibrated at the University of Illinois Urbana-Champaign (UIUC) Bioenvironmental and Structural Systems (BESS) Laboratory. Results demonstrated that the FANS-G4 was capable of measuring volumetric airflow to within 0.6% of full-scale (FS), which ranged from 15,000 to 56,000 m3 h-1

    Biofilter Media Characterization Using Water Sorption Isotherms

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    Compost material has been used extensively as a gas‐phase biofilter media for contaminant gas treatment in recent years. One of the biggest challenges in the use of this type of material is adequate control of compost moisture content and understanding its effect on the biofiltration process. The present work provides a methodology for characterization of biofilter media under low moisture conditions. Results indicated that low levels of equilibrium moisture content (EMC) were obtained for high levels of equilibrium relative humidity (ERH), i.e., 99% ERH produced EMC of approximately 20% (dry basis) at 25° C. Most bacteria struggle to survive in environments with ERH levels lower than 95%. Compost material from the same source was sieved into four compost particle size (PS) ranges to evaluate its water sorption behavior: 4.76 mm \u3e PS1 \u3e 3.36 mm \u3e PS2 \u3e 2.38 mm \u3e PS3 \u3e 2.00 mm \u3e PS4 \u3e 1.68 mm. Observed data were tested against isotherm models for their goodness‐of‐fit. Seven isotherm models were compared: (1) Langmuir; (2) Freundlich; (3) Sips; (4) Brunauer, Emmett, and Teller (BET); (5) BET for n‐layers; (6) Guggenheim, Anderson, de Boer (GAB); and (7) Henderson. In comparison with the other models, the Henderson model provided the best fit, as determined by the best combination of regression coefficient standard errors (Δ) and coefficients of determination (r2) for all four particle size ranges tested (95% confidence interval, C.I., and prediction interval, P.I.). The Henderson model was then used to test for significant differences in isotherms by particle size ranges.The four tested particle size ranges were not significantly different from each other (p \u3c 0.05), indicating similar water sorption behavior. Data from all four particle size ranges were pooled and regressed, and the minimum required moisture to maintain ERH at or above 95% was 16.41% ± 2.68% (dry basis)

    Characterizing Physical Properties of Gas-Phase Biofilter Media

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    Gas-phase biofiltration is an effective technology for reduction of odors and trace-gas contaminants. Significant contributions to the technical literature regarding the characterization of biofilter media have been generated in the past two decades. Nevertheless, the information produced has not been systematically organized. The objective of this study is to demonstrate and document methods for physical characterization of gas-phase compost biofilters (GPCB). The inclusion of moisture content, compaction, and particle size effects in the determination of media bulk density and porosity, field capacity, drying rate analysis, water sorption isotherms, and resistance to airflow is demonstrated. Results indicated that: (1) higher moisture content led to about 2% reduction in porosity after compaction; (2) biofilter media sieved into three particle size ranges (12.5 mm \u3e PSR1 \u3e 8.0 mm \u3e PSR2 \u3e 4.75 mm \u3e PSR3 \u3e 1.35 mm) produced significantly different media field capacities, i.e., 52.8% (PSR1), 61.6% (PSR2), and 72.2% (PSR3) on a wet basis; (3) a drying rate analysis provides important information regarding media-water relations and can be potentially used for in situ indirect media moisture monitoring (as shown in previous work, changes in drying rate significantly affected ammonia removal and nitrous oxide generation); (4) the Henderson isotherm can be accurately used for dry organic media to determine the minimum moisture required for microbial activity; and finally (5) the combination of high airflow and high moisture content drastically increased pressure drop up to 65-fold (6350 Pa m-1) compared to the lowest pressure drop (98 Pa m-1). Further, the research community should integrate efforts to elaborate standard methods and protocols for physical characterization of gas-phase biofilter media before and during biofilter operation
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