@article {535, title = {Thermalizing and Damping in Structural Dynamics}, journal = {Journal of Applied Mechanics}, volume = {85}, year = {2018}, month = {Aug-2018}, abstract = {

Structural damping, that is the presence of a velocity dependent dissipative term in the equation of motion, is rationalized as a thermalization process between a structure (here a beam) and an outside bath (understood in a broad sense as a system property). This is achieved via the introduction of the kinetic temperature of structures and formalized by means of an extended Lagrangian formulation of a structure in contact with an outside bath at a given temperature. Using the Nose-Hoover thermostat, the heat exchange rate between structure and bath is identified as a mass damping coefficient, which evolves in time in function of the kinetic energy/temperature history exhibited by the structure. By way of application to a simple beam structure subjected to eigen-vibrations and dynamic buckling, commonality and differences of the Nose-Hoover beam theory with constant mass damping models are shown, which permit a handshake between classical damping models and statistical mechanics-based thermalization models. The solid foundation of these thermalization models in statistical physics provides new insights into stability and instability for engineering structures. Specifically, since two systems are considered in (thermodynamic) equilibrium when they have the same temperature, we show in the case of dynamic buckling that a persistent steady-state difference in kinetic temperature between structure and bath is but indicative of the instability of the system. This shows that the kinetic temperature can serve as a structural order parameter to identify and comprehend failure of structures, possibly well beyond the elastic stability considered here.

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}, keywords = {structural dynamics; damping; Nose-Hoover Bath; kinetic temperature; dynamic buckling}, issn = {0021-8936}, doi = {10.1115/1.4040080}, url = {http://appliedmechanics.asmedigitalcollection.asme.org.libproxy.mit.edu/article.aspx?articleid=2680040}, author = {Arghavan Louhghalam and Roland Jean-Marc Pellenq and Franz-Josef Ulm} } @article {318, title = {Carbon management of infrastructure performance: Integrated big data analytics and pavement-vehicle-interactions}, journal = {Journal of Cleaner Production}, volume = {142}, year = {2017}, month = {Jan-20-2017}, pages = {956 - 964 Part: 2}, abstract = {

As a crucial part of the transportation system, roadway network provides mobility to the society and is vital for the economy. At the same time it contributes significantly to the environmental footprint during its construction, operation and maintenance. Hence, the sustainable development of our Nation\&$\#$39;s roadway system requires quantitative means to link infrastructure performance to lifecycle energy use and greenhouse gas emissions. Recent developments in mechanistic models of roughness- and deflection-induced pavement-vehicle interaction aim at providing such engineering estimates. Herein, it is demonstrated that these models when implemented at a network scale are a powerful basis for big data analytics of excess-energy consumption and carbon dioxide emissions by integrating spatially and temporally varying road conditions, pavement properties, traffic loads and climatic conditions. A novel ranking algorithm is proposed, that allows upscaling of the local carbon dioxide emissions due to pavement vehicle interaction to the size of state-wide or national sustainability goals. Implemented for 5157 lane-miles of the interstate highway system in the State of Virginia, sections contributing significantly to carbon dioxide emissions are identified. It is shown that the proposed ranking algorithm based on the inferred emission that exhibits a power-law distribution, provides the shortest path for greenhouse gas emissions savings per maintenance at network scale. That is, maintaining a few lane miles allows for a significant synergetic improvement of both infrastructure performance and environmental impact of the interstate network and helps transportation agencies in making economic and environmentally sustainable decisions.

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Fig.1. Flow of network analysis; the inputs and the output of deflection- and{\textellipsis}

Fig.2. Spatial distribution of roughness- and deflection-induced excess CO2 emissions{\textellipsis}

Fig.3. Total annual excess CO2 emissions (Tons) for a 7-year period (2007{\textendash}2013) in{\textellipsis}

Fig.4. Excess CO2 emissions in function of its rank

Fig.5. Comparison of different road selection strategies for maintenance in terms of{\textellipsis}

}, issn = {09596526}, doi = {10.1016/j.jclepro.2016.06.198}, author = {Arghavan Louhghalam and Mehdi Akbarian and Franz-Josef Ulm} } @article {320, title = {Risk of Pavement Fracture due to Eigenstresses at Early Ages and Beyond}, journal = {Journal of Engineering Mechanics}, volume = {142}, year = {2016}, month = {Dec-2016}, pages = {Article Number: 04016105 }, abstract = {

Tensile cracks significantly affect the durability of concrete pavements, leading to an increase in the costs of maintenance and rehabilitation. A model is developed that relates thermal, chemical, and hygral evolutions at small scales due to different distress mechanisms to the risk of fracture at the structural scale. The method is based on application of linear elastic fracture mechanics (LEFM) to eigenstresses that develop in infinite- and finite-length beams on an elastic foundation that represents the subgrade. Axial and bending contributions to the energy release rate are determined for a worst-case scenario of an entirely cracked pavement section in functions of material properties, structural dimensions, and eigenstress forces and moments. By way of example, the model is used to study the risk of fracture of concrete pavements due to two different mechanisms: (1)\ autogeneous shrinkage at early ages of placing the concrete and (2)\ thermal cycles at the short term and long term after a temperature change. In addition, scaling relationships are developed that provide insight into the improvement of different structural and material properties for minimizing the risk of fracture.

}, issn = {0733-9399}, doi = {10.1061/(ASCE)EM.1943-7889.0001167}, author = {Arghavan Louhghalam and Franz-Josef Ulm} } @article {147, title = {Roughness-Induced Vehicle Energy Dissipation: Statistical Analysis and Scaling}, journal = {Journal of Engineering Mechanics}, volume = {141}, year = {2015}, month = {Nov-2015}, pages = {Number: 04015046 }, abstract = {

The energy dissipated in a vehicle suspension system due to road roughness affects rolling resistance and the resulting fuel consumption and greenhouse gas emission. The key parameters driving this dissipation mechanism are identified via dimensional analysis. A mechanistic model is proposed that relates vehicle dynamic properties and road roughness statistics to vehicle dissipated energy and thus fuel consumption. A scaling relationship between the dissipated energy and the most commonly used road roughness index, the International Roughness Index (IRI), is also established. It is shown that the dissipated energy scales with IRI squared and scaling of dissipation with vehicle speed V depends on road waviness number w in the form of Vw\−2. The effect of marginal probability distribution of the road roughness profile on dissipated energy is examined. It is shown that although the marginal distribution of the road profile does not affect the identified scaling relationships, the multiplicative factor in these relationships does change from one distribution to another. As an example of practical application, the model is calibrated with the empirical HDM-4 model for different vehicle classes.

}, issn = {0733-9399}, doi = {10.1061/(ASCE)EM.1943-7889.0000944}, author = {Arghavan Louhghalam and Tootkaboni, Mazdak and Franz-Josef Ulm} } @article {313, title = {Fl{\"u}gge{\textquoteright}s Conjecture: Dissipation- versus Deflection-Induced Pavement{\textendash}Vehicle Interactions}, journal = {Journal of Engineering Mechanics}, volume = {140}, year = {2014}, month = {Aug-2014}, pages = {Article Number: 04014053 }, abstract = {

The dissipation occurring below a moving tire in steady-state conditions in contact with a viscoelastic pavement is expressed using two different reference frames: a fixed observer attached to the pavement and a moving observer attached to the pavement\–tire contact surface. The first approach is commonly referred to as dissipation-induced pavement\–vehicle interaction (PVI), the second as deflection-induced PVI. Based on the principle of frame independence, it is shown that both approaches are strictly equal, from a thermodynamic point of view, and thus predict the same amount of dissipated energy. This equivalence is illustrated through application to two pavement systems: a viscoelastic beam and a viscoelastic plate both resting on an elastic foundation. The amount of dissipated energy in the pavement structure needs to be supplied by the vehicle to maintain constant speed, thus contributing to the rolling resistance, associated excess fuel consumption, and greenhouse gas emissions. The model here proposed can be used to quantify the dissipated energy and contribute to the development of engineering methods for the sustainable design of pavements.

}, issn = {0733-9399}, doi = {10.1061/(ASCE)EM.1943-7889.0000754}, author = {Arghavan Louhghalam and Mehdi Akbarian and Franz-Josef Ulm} } @proceedings {348, title = {Pavement infrastructures footprint: The impact of pavement properties on vehicle fuel consumption}, journal = {Euro-C Conference}, volume = {COMPUTATIONAL MODELLING OF CONCRETE STRUCTURES}, year = {2014}, month = {Mar-2014}, pages = {1051-1058}, address = {MAR 24-27 2014 St Anton am Alberg, AUSTRIA}, abstract = {

A novel mechanistic model based on an infinite beam on elastic foundation is developed to
quantify the impact of pavement structural and material properties on pavement deflection and consequently on
vehicle fuel consumption. The model can also account for the effect of temperature and vehicle speed on fuel
consumption. A simplified expression for evaluating the energy dissipation for practical purposes is proposed
and used to investigate the impact of various pavement design systems on fuel consumption. GPS (General Pave-
ment Studies) sections from the FHWA\’s Long Term Pavement Performance program (FHWA 2011) are used
for this study. These sections consist of asphalt concrete (AC), portland cement concrete (PCC) and composite
pavements. The model quantifies the impact of temperature and vehicle speed on the fuel consumption and
confirms that those impacts are negligible for PCC and significant for AC pavements due to their viscoelasticity.

}, url = {https://cshub.mit.edu/sites/default/files/documents/louhghalam-Euro-C-2014.pdf}, author = {Arghavan Louhghalam and Mehdi Akbarian and Franz-Josef Ulm}, editor = {Bicanic, N and Mang, H and Meschke, G} } @article {149, title = {Roughness-induced Pavement-Vehicle Interactions Key Parameters and Impact on Vehicle Fuel Consumption}, journal = {Transportation Research Record: Journal of the Transportation Research Board}, volume = {2525}, year = {2014}, month = {Dec-30-2014}, pages = {62 - 70}, abstract = {

Pavement roughness affects rolling resistance and thus vehicle fuel consumption. When a vehicle travels at constant speed on an uneven road surface, the mechanical work dissipated in the vehicle\’s suspension system is compensated by vehicle engine power and results in excess fuel consumption. This dissipation depends on both road roughness and vehicle dynamic characteristics. This paper proposes, calibrates, and implements a mechanistic model for roughness-induced dissipation. The distinguishing feature of the model is its combination of a thermodynamic quantity (energy dissipation) with results from random vibration theory to identify the governing parameters that drive the excess fuel consumption caused by pavement roughness, namely, the international roughness index (IRI) and the waviness number, w (a power spectral density parameter). It is shown through sensitivity analysis that the sensitivity of model output, that is, excess fuel consumption, to the waviness number is significant and comparable to that of IRI. Thus, introducing the waviness number as a second roughness index, in addition to IRI, allows a more accurate quantification of the impact of surface characteristics on vehicle fuel consumption and the corresponding greenhouse gas emissions. This aspect is illustrated by application of the roughness\–fuel consumption model to two road profiles extracted from FHWA\’s Long-Term Pavement Performance database.

}, issn = {0361-1981}, doi = {10.3141/2525-07}, author = {Arghavan Louhghalam and Mehdi Akbarian and Franz-Josef Ulm} } @article {304, title = {Scaling Relationships of Dissipation-Induced Pavement-Vehicle Interactions}, journal = {Transportation Research Record: Journal of the Transportation Research Board}, volume = {2457}, year = {2014}, month = {Jan-2014}, pages = {95 - 104}, abstract = {

Rolling resistance is one of the key factors that affect the fuel efficiency of the national pavement system. In addition to pavement texture and pavement roughness, the dissipation of mechanical work provided by the vehicle because of viscous deformation within the pavement structure has been recognized as a relevant factor contributing to the environmental footprint of pavement systems. This dissipation depends on material and structural parameters that can be optimized to increase the fuel efficiency of pavements. Identifying the key material and structural parameters that drive this dissipation is the focus of this paper. This identification is achieved by a combination of dimensional analysis and model-based simulations of the dissipation of a viscoelastic beam on an elastic foundation. For linear viscoelastic systems, the dissipation is found to scale with the square of the vehicle weight and with the inverse of the viscous relaxation time, in addition to distinct power relations of top-layer stiffness, thickness, and subgrade modulus. These scaling relations can be used by pavement engineers to reduce such pavement-inherent dissipation mechanisms and increase the fuel efficiency of a pavement design. An example shows the application of these scaling relations with data extracted from FHWA\&$\#$39;s Long-Term Pavement Performance database for seven road classes. The scaling relations provide a means for evaluating the performance of the various road classes in terms of the fuel efficiency related to dissipation.

}, issn = {0361-1981}, doi = {10.3141/2457-10}, author = {Arghavan Louhghalam and Mehdi Akbarian and Franz-Josef Ulm} }