scholarly journals The Impact of a Mill Policy to Discourage Overweight Log Trucks

2004 ◽  
Vol 28 (3) ◽  
pp. 132-136 ◽  
Author(s):  
Ian P. Conradie ◽  
W. Dale Greene ◽  
Michael L. Clutter
Keyword(s):  
Minimal Amount ◽  
Vehicle Weight ◽  
Legal Limit ◽  
Gross Vehicle Weight ◽  
Truck Weight ◽  
The Impact

Abstract In Jan. 2002, Rayonier adopted a new truck weight policy at their Georgia mills to discourage gross overloading of trucks. Under this policy, logging contractors were paid a minimal amount per ton for weights exceeding 44 tons. To evaluate the effectiveness of this policy, we compared the weights of all trucks delivering wood to three company mills in Jan. 2001 (before the new policy) with the weights of all trucks delivering to the same three mills in Jan. 2002 (the first month the policy was used). This policy was very effective in a short amount of time. The percentage of trucks with gross vehicle weights exceeding 44 tons dropped from 5.56 to 3.01% after the new policy took effect and this improvement was seen within a week. We also observed other improvements in trucking performance. The percentage of loads within 5% of the legal limit increased from 45.8 to 57.4% through dramatic reductions in the percentage of underloaded trucks. In fact, after the new policy took effect, average gross vehicle weight and the average truck payload both increased due to this reduction in the percentage of underloaded trucks. South. J. Appl. For. 28(3):132–136.

Perceptions of Log Truck Weight Regulations Among Loggers and Forest Industry in Georgia, USA

2021 ◽  
Author(s):  
Joseph L Conrad
Keyword(s):  
The State ◽  
Transportation Costs ◽  
Forest Industry ◽  
Public Infrastructure ◽  
Truck Traffic ◽  
Telephone Surveys ◽  
Southern States ◽  
Vehicle Weight ◽  
Gross Vehicle Weight ◽  
Truck Weight

Abstract Georgia and other southern states have far lower gross vehicle weight (GVW) limits for log trucks than other US regions and other countries. Low GVW limits result in high hauling costs and truck traffic. In 2020, including tolerances, five-axle log tractor-trailers were allowed 38,102 kg (84,000 lb) GVW in Georgia. Telephone surveys of 30 loggers and 32 forest industry representatives from the state of Georgia were conducted to measure perceptions of weight regulations and assess support for alternative weights and configurations. The four alternatives included five axles, 39,916 kg (88,000 lb); six axles, 41,277 kg (91,000 lb); six axles, 45,359 kg (100,000 lb); and seven axles, 45,359 kg (100,000 lb) GVW. The majority of loggers and forest industry representatives stated that GVW limits for log trucks were too low. The average preferred GVW limits were 39,621 kg (87,350 lb) and 40,545 kg (89,387 lb) for loggers and forest industry, respectively. Loggers and forest industry supported the five-axle 39,916 kg (88,000 lb) configuration whereas many loggers opposed both 45,359 kg (100,000 lb) configurations. Loggers, forest industry, and policymakers should work to modernize weight laws to reduce hauling costs, maintain or improve safety, and protect public infrastructure. Study Implications Increasing gross vehicle weight (GVW) limits in combination with adding axles to tractor-trailers has been demonstrated to reduce both timber transportation costs and damage to public roads. This study found that loggers and forest industry supported additional GVW but were hesitant to support configurations that would necessitate upgrading log truck fleets. If Georgia is to make its weight limits competitive regionally and internationally, it will be necessary to clearly communicate the benefits of heavier trucks with more axles to skeptical loggers.

Towards 2222, science fiction or an educated guess for the design of bridges?

2019 ◽  
Author(s):  
Rob Vergoossen
Keyword(s):  
Virtual Reality ◽  
Science Fiction ◽  
Renewable Energies ◽  
Railroad Bridges ◽  
Vehicle Weight ◽  
The World ◽  
Gross Vehicle Weight ◽  
The Impact ◽  
And Robotics ◽  
Far Future

<p>About 200 years ago the first railroad bridges were build, followed almost 100 years later by bridges for cars and trucks. Since the first cars and trucks, traffic has changed. Up to now this change is mostly an increase in intensity and axle and gross vehicle weight of trucks. But soon mobility will change.</p><p>When designing a bridge for a lifespan of 200 years there are a lot of uncertainties to deal with.</p><p>Will there be more vehicles due to easier transport, or will there be less because of a reducing population, virtual reality and robotics? There are a lot of construction activities going on in the world, but when will this change and what is the impact on mobility and transportation? The innovation in technology will change the use of the transport, which will make it more efficient, but is this also efficient for bridges? And what will be the effect of renewable energies and reducing CO2 on the usage of bridges? A lot of unknowns and only future will tell us what exactly will happen.</p><p>In this paper we give some scenarios on possible changes in the near and far future and how this can possibly influence the way we design our bridges today.</p>

Truck weights as a function of regulatory limits

1990 ◽  
Vol 17 (1) ◽  
pp. 45-54 ◽  
Author(s):  
A. Clayton ◽  
R. Plett
Keyword(s):  
Key Words ◽  
Vehicle Weight ◽  
Regulatory Limits ◽  
Weight Distributions ◽  
Gross Vehicle Weight ◽  
Important Input ◽  
Truck Weight

Models are developed for the gross vehicle weight and axle weight distributions of laden trucks as a function of governing weight limits. The models are based on truck weight surveys conducted in Manitoba between 1972 and 1986, a period of changing weight limits. They are developed for 2-axle trucks, 3-axle trucks, 5-axle (3-S2) tractor-semitrailers, 7-axle (3-S2-2) A-trains, and 7-axle (3-S2-S2) B-trains. The models can provide important input to the analysis of pavement loadings (and costs), given particular weight limits or changes in weight limits. They can also provide useful input to estimates of the relative benefits of alternative weight limit regimes. Key words: truck weights, weight limits.

scholarly journals Retrospective Longitudinal Study of the Impact of Truck Weight Regulatory Changes on Operating Gross Vehicle Weights

2021 ◽  
pp. 036119812199550
Author(s):  
Amanda Pushka ◽  
Jonathan D. Regehr
Keyword(s):  
Longitudinal Study ◽  
Current Knowledge ◽  
Regulatory Change ◽  
The Road ◽  
Regulatory Changes ◽  
Gross Vehicle Weight ◽  
Truck Size And Weight ◽  
Truck Weight ◽  
The Impact ◽  
Weight Data

Three primary policy changes on truck size and weight occurred in Canada over the past five decades: the 1974 Western Canadian Highway Strengthening Program, the 1988 Roads and Transportation Association of Canada Memorandum of Understanding on Heavy Vehicle Weights and Dimensions, and ongoing special permitting of longer combination vehicles. These regulatory changes influenced the gross vehicle weight (GVW) of the predominant truck configurations operating on principal Canadian highways. Using a unique time-series of truck weight data, this retrospective longitudinal study contributes insights about the magnitude and timing of the impacts of truck weight regulatory changes on operating GVWs that address current knowledge gaps and persistent uncertainties in models used to predict and evaluate truck weight regulatory changes. The analysis reveals that carriers hauling heavy (i.e., weigh-out) commodities adapt immediately to increases in GVW limits if there is no need to purchase new vehicles. When a regulatory change coincides with the introduction of a new, more productive vehicle configuration, the uptake of the new vehicle lags behind the regulatory change by a few years. Finally, configurations exhibit different GVW distributions and responses to increased GVW limits depending on whether the configurations are well suited for hauling weigh-out or cube-out commodities. This differential response demonstrates how regulations facilitate fleet diversity within the trucking industry’s approach to the road freight transport task.

scholarly journals Evaluation of the Impact of Timber Truck Configuration and Tare Weight on Payload Efficiency: An Australian Case Study

Forests ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 855
Author(s):  
Mark W. Brown
Keyword(s):  
Load Management ◽  
Vehicle Design ◽  
Forest Industry ◽  
Post Operation ◽  
Gross Vehicle Weight ◽  
Australian Case ◽  
Trends Over Time ◽  
The Impact

The forest industry tends to plan, and model transportation costs based on the potential payload benefits of increased legal gross vehicle weight (GVW) by deploying different configurations, while payload benefits of a configuration can be significantly influenced by the vehicle design tare weight. Through this research the relative benefit of increased legal GVW of different configurations is compared across Australia over a 13-year period from 2006 to 2019, by examining data collected post operation across multiple operations. This approach is intended to offer realistic insight to real operations not influenced by observation and thus reflect long-term operating behaviour. The inclusion of the three most common configuration classes in Australian forestry over a 13-year period has also allowed the exploration of load management between configurations and potential trends over time. When considering the legal GVW and the tare weight impacts across the fleets, the semi-trailer has an 8 t payload disadvantage compared to B-Doubles and 19.6 t disadvantage compared to road trains.

Vehicles and gross vehicle weight

2021 ◽  
pp. 11-46
Author(s):  
Andrzej Nowak ◽  
Jacek Chmielewski ◽  
Sylwia Stawska
Keyword(s):  
Vehicle Weight ◽  
Gross Vehicle Weight

scholarly journals Research on Carbon Emissions of Electric Vehicles throughout the Life Cycle Assessment Taking into Vehicle Weight and Grid Mix Composition

Energies ◽  
2019 ◽  
Vol 12 (19) ◽  
pp. 3612 ◽  
Author(s):  
Yanmei Li ◽  
Ningning Ha ◽  
Tingting Li
Keyword(s):  
Life Cycle Assessment ◽  
Life Cycle ◽  
Electric Vehicles ◽  
Carbon Emissions ◽  
Linear Regression Analysis ◽  
Clean Energy ◽  
Assessment Method ◽  
Weight Class ◽  
Vehicle Weight ◽  
The Impact

To study the impact of the promotion of electric vehicles on carbon emissions in China, the full life carbon emissions of electric vehicles are studied on the basis of considering such factors as vehicle weight and grid mix composition, and fuel vehicles are added for comparison. In this paper, we collect data for 34 domestic electric vehicles, and linear regression analysis is used to model the relationship between vehicle weight and energy consumption. Then, a Hybrid Life Cycle Assessment method is used to establish the life cycle carbon emission calculation model for electric vehicles and fuel vehicles. Finally, the life cycle carbon emissions of electric vehicles and fuel vehicles under different electrical energy structures are discussed using scenario analysis. The results show that under the current grid mix composition in China, the carbon emissions of electric vehicles of the same vehicle weight class are 24% to 31% higher than that of fuel vehicles. As the proportion of clean energy in the grid mix composition increases, the advantages of electric vehicles to reduce carbon emissions will gradually emerge.

Comparison of Machine Learning Algorithms in the Interpolation and Extrapolation of Flame Describing Functions

2019 ◽  
Author(s):  
Michael McCartney ◽  
Matthias Haeringer ◽  
Wolfgang Polifke
Keyword(s):  
Machine Learning ◽  
Gaussian Processes ◽  
Spline Interpolation ◽  
Learning Algorithms ◽  
Predictive Performance ◽  
Machine Learning Algorithms ◽  
Test Time ◽  
Minimal Amount ◽  
Data Points ◽  
The Impact

Abstract This paper examines and compares commonly used Machine Learning algorithms in their performance in interpolation and extrapolation of FDFs, based on experimental and simulation data. Algorithm performance is evaluated by interpolating and extrapolating FDFs and then the impact of errors on the limit cycle amplitudes are evaluated using the xFDF framework. The best algorithms in interpolation and extrapolation were found to be the widely used cubic spline interpolation, as well as the Gaussian Processes regressor. The data itself was found to be an important factor in defining the predictive performance of a model, therefore a method of optimally selecting data points at test time using Gaussian Processes was demonstrated. The aim of this is to allow a minimal amount of data points to be collected while still providing enough information to model the FDF accurately. The extrapolation performance was shown to decay very quickly with distance from the domain and so emphasis should be put on selecting measurement points in order to expand the covered domain. Gaussian Processes also give an indication of confidence on its predictions and is used to carry out uncertainty quantification, in order to understand model sensitivities. This was demonstrated through application to the xFDF framework.

General Principles for Sensory Coding

2018 ◽  
Author(s):  
Tatyana O. Sharpee
Keyword(s):  
Sensory System ◽  
Sensory Systems ◽  
Multiple Delays ◽  
Minimal Amount ◽  
Sensory Coding ◽  
Trade Offs ◽  
Almost All ◽  
Comprehensive Framework ◽  
State Of The Environment ◽  
The Impact

Sensory systems exist to provide an organism with information about the state of the environment that can be used to guide future actions and decisions. Remarkably, two conceptually simple yet general theorems from information theory can be used to evaluate the performance of any sensory system. One theorem states that there is a minimal amount of energy that an organism has to spend in order to capture a given amount of information about the environment. The second theorem states that the maximum rate with which the organism can acquire resources from the environment, relative to its competitors, is limited by the information this organism collects about the environment, also relative to its competitors. These two theorems provide a scaffold for formulating and testing general principles of sensory coding but leave unanswered many important practical questions of implementation in neural circuits. These implementation questions have guided thinking in entire subfields of sensory neuroscience, and include: What features in the sensory environment should be measured? Given that we make decisions on a variety of time scales, how should one solve trade-offs between making simpler measurements to guide minimal decisions vs. more elaborate sensory systems that have to overcome multiple delays between sensation and action. Once we agree on the types of features that are important to represent, how should they be represented? How should resources be allocated between different stages of processing, and where is the impact of noise most damaging? Finally, one should consider trade-offs between implementing a fixed strategy vs. an adaptive scheme that readjusts resources based on current needs. Where adaptation is considered, under what conditions does it become optimal to switch strategies? Research over the past 60 years has provided answers to almost all of these questions but primarily in early sensory systems. Joining these answers into a comprehensive framework is a challenge that will help us understand who we are and how we can make better use of limited natural resources.

scholarly journals Improving Log Trucking Efficiency by Using In-Woods Scales

2011 ◽  
Vol 35 (4) ◽  
pp. 178-183 ◽  
Author(s):  
Ryan P. Reddish ◽  
Shawn A. Baker ◽  
W. Dale Greene
Keyword(s):  
Coefficient Of Variation ◽  
Forest Products ◽  
Fuel Prices ◽  
Southern States ◽  
Vehicle Weight ◽  
Gross Vehicle Weight ◽  
The Mean ◽  
Weight Data

Abstract We evaluated weight data from 47,953 truckloads of wood delivered to forest products mills in nine southern states to determine the effect of in-woods scale use on reducing the variability of net and gross weights. Four mill-owning companies provided the data and indicated whether in-woods scales were used for each load. We used these data to compare the mean tare, net, and gross weights of truckloads using scales to those not using scales. Trucks using scales had average tare weights only 108 lb greater, but their net payload averaged 1,799 lb higher than trucks not using scales. The coefficient of variation for the net payload was 38% lower for loads with scales than those without (P < 0.001). Individual southern states have different regulations regarding maximum gross vehicle weight (GVW), so we calculated a GVW index to remove state bias and allow comparisons of loads across states. Loads using scales were within 2% of the legal maximum GVW 54% of the time compared with 30% for loads not weighed in-woods. We estimated haul costs for trucks using scales at $7.44 per ton, compared with $7.74 per ton for trucks not using scales (P < 0.001). We found that 11% of loads with in-woods scales had haul costs exceeding $8.00 per ton, compared with 32% of loads not using scales. Across all data, scales represent a 4% savings on per-ton haul costs with even greater savings available as fuel prices increase.

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