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Varshney K.,Taitem Engineering | Chang S.,Cornell University | Wang Z.J.,Cornell University
Physical Review E - Statistical, Nonlinear, and Soft Matter Physics | Year: 2013

Falling parallelograms exhibit coupled motion of autogyration and tumbling, similar to the motion of falling tulip seeds, unlike maple seeds which autogyrate but do not tumble, or rectangular cards which tumble but do not gyrate. This coupled tumbling and autogyrating motion are robust, when card parameters, such as aspect ratio, internal angle, and mass density, are varied. We measure the three-dimensional (3D) falling kinematics of the parallelograms and quantify their descending speed, azimuthal rotation, tumbling rotation, and cone angle in each falling. The cone angle is insensitive to the variation of the card parameters, and the card tumbling axis does not overlap with but is close to the diagonal axis. In addition to this connection to the dynamics of falling seeds, these trajectories provide an ideal set of data to analyze 3D aerodynamic force and torque at an intermediate range of Reynolds numbers, and the results will be useful for constructing 3D aerodynamic force and torque models. Tracking these free falling trajectories gives us a nonintrusive method for deducing instantaneous aerodynamic forces. We determine the 3D aerodynamic forces and torques based on Newton-Euler equations. The dynamical analysis reveals that, although the angle of attack changes dramatically during tumbling, the aerodynamic forces have a weak dependence on the angle of attack. The aerodynamic lift is dominated by the coupling of translational and rotational velocities. The aerodynamic torque has an unexpectedly large component perpendicular to the card. The analysis of the Euler equation suggests that this large torque is related to the deviation of the tumbling axis from the principle axis of the card. © 2013 American Physical Society.

Varshney K.,Taitem Engineering | Poddar K.,Indian Institute of Technology Kanpur
Theoretical and Applied Climatology | Year: 2011

Accurate predictions of turbulent characteristics in the atmospheric boundary layer (ABL) depends on understanding the effects of surface roughness on the spatial distribution of velocity, turbulence intensity, and turbulence length scales. Simulation of the ABL characteristics have been performed in a short test section length wind tunnel to determine the appropriate length scale factor for modeling, which ensures correct aeroelastic behavior of structural models for non-aerodynamic applications. The ABL characteristics have been simulated by using various configurations of passive devices such as vortex generators, air barriers, and slot in the test section floor which was extended into the contraction cone. Mean velocity and velocity fluctuations have been measured using a hot-wire anemometry system. Mean velocity, turbulence intensity, turbulence scale, and power spectral density of velocity fluctuations have been obtained from the experiments for various configuration of the passive devices. It is shown that the integral length scale factor can be controlled using various combinations of the passive devices. © 2011 Springer-Verlag.

Varshney K.,Taitem Engineering | Poddar K.,Indian Institute of Technology Kanpur
Theoretical and Applied Climatology | Year: 2012

Artificial neural network (ANN) modeling has been performed to predict turbulent boundary layer characteristics for rough terrain based on experimental tests conducted in a boundary-layer wind tunnel to simulate atmospheric boundary layer using passive roughness devices such as spires, barriers, roughness elements on the floor, and slots in the extended test section. Different configurations of passive devices assisted to simulate urban terrains. A part of the wind tunnel test results are used as training sets for the ANN, and the other part of the test results are used to compare the prediction results of the ANN. Two ANN models have been developed in this study. The first one has been used to predict mean velocity, turbulence intensity, and model length scale factor. Results show that ANN is an efficient, accurate, and robust modeling procedure to predict turbulent characteristics of wind. In particular, it was found that the ANN-predicted wind mean velocities are within 4. 7%, turbulence intensities are within 6. 2%, and model length scale factors are within 3. 8% of the actual measured values. In addition, another ANN model has been developed to predict instantaneous velocities that enables calculating the power spectral density of longitudinal velocity fluctuations. Results show that the predicted power spectra are in a good agreement with the power spectra obtained from measured instantaneous velocities. © 2011 Springer-Verlag.

News Article | September 26, 2016

Although solar can supply electricity for a fraction of the cost of conventional sources, there are great fluctuations in the market prices. The cost of an average installation ranges from $21,104 on Long Island to $11,715 in the Watertown area. A new report from Solar to the People gives homeowners a guide to understand the differences when pricing solar in New York state. Ryan Willemsen, of Solar to the People, gave several reasons for the range of installation prices. “By far the biggest differences are due to the fact that there are strong per watt rebates (currently $0.40/watt) available in Upstate NY that are no longer available in the Long Island region. These rebates are through the NY-Sun Incentive Program,” he explained. Comparing Long Island to Watertown, Willemsen said the installations tend to be slightly larger (9.59 kW vs 8.32 kW during the first half of 2016). Wages in rural upstate New York areas are also much lower than the relatively high-cost Long Island. Long Island is an extremely transmission-constrained region, and while obviously power prices are fluctuating all the time, National Grid (the supplier in upstate NY) and the Long Island Power Authority (one of the two utilities in Long Island) state that the power in Long Island is more than 3x more expensive per kWh. “The average cost of purchasing home solar in New York in the first half of 2016 was $16,426, after rebates and incentives,” emailed Willemsen. During the first half of the year, this average cost of solar installed across the state amounted to $1,973/kW (kilowatt) for a 8.32 kW installation, after incentives and rebates. Willemsen said it is difficult to calculate how much the average homeowners would save by installing solar panels. “It really depends on a LOT of factors (how much you paid for panels, how much sun you’re getting, what time of year, what your panels are producing at, what the power rates are etc). However, in both regions based on some simplistic calcs (complex are not always better) that I ran back of the envelope, one would save roughly 66% on power costs over 20 years with panels in the Watertown area, while Long Island would save roughly 40%,” he explained. He added, “As of today, the NYSERDA NY-Sun database had 68,721 installations of less than 200 kW. While this database doesn’t include everything in New York (state), it gets a very significant portion of the installations, and is the most comprehensive data set available.” Photo Credits: An installation in the snow courtesy Taitem Engineering, New York; Map from Solar for the People; Screenshots from National Grid & Long Island Power Authority — obtained through Power for the People; List & bar chart of New York Prices courtesy Power for the People; Installing solar panels on a barn in upstate New York (two photos) courtesy Kasselman Solar Buy a cool T-shirt or mug in the CleanTechnica store!   Keep up to date with all the hottest cleantech news by subscribing to our (free) cleantech daily newsletter or weekly newsletter, or keep an eye on sector-specific news by getting our (also free) solar energy newsletter, electric vehicle newsletter, or wind energy newsletter.

Shapiro I.,Taitem Engineering
ASHRAE Journal | Year: 2011

A study was conducted to examine the efficiency of energy audits and the measures that can be taken to improve their outcomes. An audit had to have an improvement with savings more than twice as high as reasonable. The criterion for this problem was for a cost estimate to be less than half what might be reasonable for a specific improvement. The energy audit that recommended the long-payback wind turbine missed such common improvements as attic insulation, air sealing, lighting controls, and laundry improvements. Audits in single-family residential buildings are more likely to have problems, averaging almost 8.1 out of 10 types of problems per audit, compared to audits in commercial buildings that averaged only 4.6 types of problems per audit. Nine out of 10 common problems are evident in over 50% of energy audits, and the two most common problems appear in almost 80% of energy audits. The two biggest problems are unfortunately complementary.

Shapiro I.M.,Taitem Engineering
ASHRAE Journal | Year: 2012

Small office buildings run the risk of being overlooked and under served for energy improvements because of their size. Common traits between small and large offices include their main space types: primarily desk/office space, but also conference rooms, storage/filing, kitchenettes and break rooms, bathrooms, corridors, stairwells, copy/print areas, and computer rooms. Small office buildings typically do not have energy management systems, so control improvements need to be examined in a different way than for big buildings. Small office buildings also often use residential HVAC equipment, or small commercial equipment such as packaged rooftop units, almost all of which are direct-expansion cooling systems. Small offices also often tend to be integrated as part of a mixed-use building, for example, as one floor of an apartment building, or as one section of a strip mall. Small offices are also often just old houses, with features such as pitched roofs and basements. This brings us back to the importance of envelope energy losses and improvement opportunities, as well as to the important emerging improvements relating to reducing distribution losses.

Varshney K.,Taitem Engineering | Shapiro I.,Taitem Engineering | Bronsnick Y.,Taitem Engineering | Holahan J.,Taitem Engineering
HVAC and R Research | Year: 2011

Vertical stack water source heat pumps are widely used to provide both comfort cooling and heating to buildings. A problem of air bypass, in which some return air does not pass over the indoor coil of the heat pump, was encountered, causing performance degradation of the heat pumps. This article quantifies the air bypass problem in vertical stack water source heat pumps and the associated impacts. Field testing at five different sites was performed, and results show that air bypass occurred in all five installations. Three methods are proposed to detect and diagnose the air bypass problem. By sealing air bypass locations after the diagnostics, the improvement in cooling efficiency ranged from ∼7% to 17% and averaged 12.8%, and the improvement in heating efficiency ranged from ∼16% to 19% and averaged 17.5%. Based on the locations of air bypass, it is shown that ∼55% of bypassed air was passing through the locations, which are common in all types of heat pumps. Copyright © 2011 American Society of Heating, Refrigerating and Air-Conditioning Engineers, Copyright © 2011 American Society of Heating, Refrigerating and Air-Conditioning Engineers.

Shapiro I.,Taitem Engineering
ASHRAE Journal | Year: 2010

A report of high energy savings at a multifamily building in Ithaca, New York, US, resulting from the replacement of an old steam boiler with a new hot water boiler, led to a survey of similar completed projects in the city to assess their high energy saving potential. An evaluation of water use in steam-heated buildings was conducted and fifty buildings were surveyed for which water use records were available. Water use in steam-heated buildings was found to be 79% higher than in buildings not heated with steam, demonstrating more than the national average for residential water consumption per person. Preretrofit and post-retrofit utility bills were analyzed for seven multifamily residential buildings where old steam boilers were replaced and for which utility bills were available. Six of the seven buildings had participated in a program of the New York State Energy Research and Development Authority (NYSERDA).

Varshney K.,Taitem Engineering | Rosa J.E.,Taitem Engineering | Shapiro I.,Taitem Engineering
International Journal of Green Energy | Year: 2012

Windows are an essential part of buildings due to the requirement for natural light, views, and fresh air. However, windows are thermally the weakest bridge in a building due to their high thermal conductivity. Therefore, window U-factor (thermal transmittance) information is indispensable in calculating the overall energy load of a building. U-factors of windows, however, are difficult to obtain on-site because the label mounted on a window exhibiting its U-factor is typically removed after its installation. Further, it is almost impossible to detect any of a variety of window failures, such as the loss of insulating gases, leaky or cracked windows, and localized air leakage, simply by visual inspection. In this study, a novel technique to measure window U-factor in the field by measuring four temperatures (interior and exterior air temperatures, and interior and exterior window surface temperatures) is presented. Experimental and field tests on various types of full-scale windows have been performed to obtain their field-measured U-factors. Experimental results show that the field-measured U-factors match within 8% of the rated U-factors of the windows. Several assemblies combining storm windows with single- or double-pane windows were tested and the combined U-factors of the assemblies were measured and the readings were compared with the U-factors estimated by ASHRAE. In another test, argon from a double-pane window was removed deliberately and results confirmed the leakage using the proposed method. In addition, field tests at five different buildings were performed and the comparison between measured and rated (or estimated) U-factors is presented. © 2012 Taitem Engineering.

Varshney K.,Taitem Engineering
Journal of Thermal Science | Year: 2012

Boundary-layer wind tunnel provides a unique platform to reproduce urban, suburban and rural atmospheric boundary layer (ABL) by using roughness devices such as vortex generators, floor roughness, barrier walls, and slots in the extended test-section floor in the contraction cone. Each passive device impacts wind properties in a certain way. In this study, influence of various passive devices on wind properties has been investigated. Experiments using eighteen different configurations of the passive devices have been carried out to simulate urban, sub-urban, and rural climate conditions in a boundary-layer wind tunnel. The effect of each configuration on the wind characteristics is presented. It was found that higher barrier height and more number of roughness elements on the floor, generated higher turbulence and therefore higher model scale factors were obtained. However, increased slot width in the extended test-section floor in the contraction cone of the wind tunnel seemed to have a little effect on wind characteristics. © Science Press and Institute of Engineering Thermophysics, CAS and Springer-Verlag Berlin Heidelberg 2012.

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