omniomni/omni-engineering huggingface dataset:
In Einstein's theory of special relativity, the relativistic momentum is concerned with the motion of a particle of relativistic mass whose velocity approaches the speed of light, but not equal to the speed of the light. An electromagnetic photon is a massless particle and its momentum is concerned with the motion of the massless photon whose velocity is equal to the speed of light. This paper focuses on the momentum of massless photon and a particle with relativistic mass. Keywords: relativistic motion , momentum equation, speed of light 1. Introduction Electromagnetic radiation is described in terms of a stream of massless particles, called photons, each travelling in a wave -like pattern at the speed of light . Each photon carries a certain amount of energy in the waveform. In Einstein’s theory of speci al relativity, the relativistic mass [1-3] plays an important role in the mass -energy equivalence. In electromagnetic spectrum, the rest mass and relativistic mass of photon are equal to zero. Thus, the velocity of any particle with rest mass or relativistic mass cannot be equal to the speed of light [4-6]. 2. Einstein’s Mass -Energy Equation The equation of relativistic mas states that 𝑚=𝑚0 √1−𝑣2 𝑐2. Where,  the rest mass of the body is 𝑚0  the velocity of particle in motion is 𝑣  the speed of light is 𝑐 Then, let us derive the mass -energy equivalence using the equation of relativistic mass. 𝑚2=𝑚02 1−𝑣2 𝑐2⟹𝑚2𝑐2−𝑚2𝑣2−𝑚02𝑐2=0,where 𝑚0 and 𝑐 are constants . By differentiating this equation with respect to time, we get 𝑐22𝑚𝑑𝑚 𝑑𝑡−2𝑚𝑣𝑑(𝑚𝑣) 𝑑𝑡=0 𝑣𝑑(𝑚𝑣) 𝑑𝑡=𝑐2𝑑𝑚 𝑑𝑡 (1) Page | 2 The equation of kinetic energy states that E=1 2𝑚𝑣2,where 𝑚 is mass and 𝑣 is velocity . By differentiating the equation of kinetic energy with respect to time, we get 𝑑𝐸 𝑑𝑡=1 2(𝑚2𝑣𝑑𝑣 𝑑𝑡)⟹𝑑𝐸 𝑑𝑡=𝑚𝑣𝑑𝑣 𝑑𝑡=𝐹𝑣=𝑣𝑑(𝑚𝑣) 𝑑𝑡=𝑣𝑑𝑝 𝑑𝑡, where the acceleration (𝑎)=𝑑𝑣 𝑑𝑡,force (𝐹)=𝑚𝑎,and momentum (𝑝)=𝑚𝑣. The rate of kinetic energy with respect to time is given below: 𝑑𝐸 𝑑𝑡=𝐹𝑣=𝑣𝑑(𝑚𝑣) 𝑑𝑡. (2) From the equations (1) and (2), we obtain 𝑑𝐸 𝑑𝑡=𝐹𝑣=𝑣𝑑(𝑚𝑣) 𝑑𝑡=𝑐2𝑑𝑚 𝑑𝑡⟹𝑑𝐸=𝑐2𝑑𝑚 Here , 𝑐2𝑑𝑚 is equal to the kinetic energy ( 𝑑𝐸). Integrating the equation 𝑑𝐸=𝑐2𝑑𝑚, ∫𝑑𝐸𝐸 0=𝑐2∫𝑑𝑚𝑚 0, Now, we conclude that 𝐸=𝑚𝑐2, which is mass -energy equivalence. 3. Momentum Equation The momentum ( 𝑝′) of a massless photon is equal to the Planck constant ( ℎ) multiplied by the frequency ( 𝑓) 𝑝′=ℎ𝑓 The Einstein mass -energy equation is: 𝐸=𝑚𝑐2=(𝑚𝑐)×𝑐=𝑝𝑐, where momentum (𝑝)=𝑚𝑐 and 𝑚 is relativistic mass . 𝑝=𝑝′, which is a contradiction. But 𝑝<𝑝′is true because the momentum ( 𝑝) of a particle with relativistic mass must be less than the momentum ( 𝑝′) of a massless particle (photon). 4. Conclusion In this article, the momentum of a massless particle (photon) and a particle with mass has been discussed in detai l. Also, it was shown that the momentum of a massless photon is not equal to the momentum of a particle with relativistic mass.
present s an advanced framework for the validation of such model s. MRI based indentation experiments are proposed during which dynamic indentation force, 3D dynamic tissue deformation, tissue geometry and fibre architecture are recorded. Following inverse Finite Element Analysis (FEA ) of the experimental boundary condi tions the parameters of an appropriate constitutive law can be optimised. The framework presented allow s for the first time for the non-invasive evaluation of detailed non - linear , anisotropic and viscoelastic material laws. Methods Using newly developed computer controlled MRI compatible soft tissue indentor , a cylindrical gel phantom (with known mechanical properties) and the upper arm region of a volunteer w ere subjected to transverse indentation (Fig.1A -C). Force was recorded with a custom made 100Hz optical force sensor. During indentation dynamic 3D tissue deformation is recorded through the application of novel dynamic tagged MRI methods (Fig.1C) (dynamically optimised version of [Moerman, 2011 ]) and fully automatic Gabor filtering based post-process ing. Prior to indentation anatomical , and for the volunteer tests also diffusion tensor [Froeling, 2010 ], MRI we re used to record the tissue geometry and muscle fibre architecture (Fig.1.E) . Using custom made segmentation software these could be converted to detailed FEA models where for the volunteer skin, adipose and muscle are accounted for (bone is modelled via supported core nodes ). The silicone gel phantom and human s kin and adipose tissue are modelled as Ogden hyperelastic . Muscle was modelled using a novel constitutive model : the Gaussian modulated spherical fibre d istribution Ogden hyperelastic. Results Fig.1B shows f orce displacement history curves for repeated indentations sampled at 100Hz which demonstrate tissue viscoelasticity . Fig.1 D shows a dense (3mm grid , 3.6 Hz) tagged MRI derived dynamic 3D displacement field. Following segmentation of anatomical MRI accurate FEA model s could be constructed and for the volunteer model (Fig1.F left) fibre directions could be mapped for each element . For t he phantom model (Fig1.F right) preliminary results show appropriate material parameters can be derived following inverse FEA based optimisation of the experimental force and deformation boundary conditions . Figure 1: The non -invasive analysis framework Discussion and Conclusions An experimental and computational framework is presented consist ing of the following unique features : 1) a novel computer controlled MRI compatible indento r, 2) a high speed (100Hz) optical force sensor , 3) high resolution (3mm ) tagged MRI based dynamic (3.6Hz) 3D tissue deformation measurement and 4) anatomical and diffusion tensor MRI based FEA model construction where fibre directions can be mapped for each element . This framework allow s, for the first time , for the non-invas ive validation of detailed anisotropic, non -linear and viscoelastic constitutive laws. Preliminary results on a phantom demonstrate the use of the framework for inverse FEA based material parameter determin ation . Results for human inverse FEA will be prese nted.
13 The current study aims to present a model to characterize changes in network traffic flows as a 14 result of implementing connected and autonomous vehicle (CA V) technology based on traffic 15 network and built -environment characteristics. To develop such a model, first, POLARIS agent - 16 based modeling platform is used to predict change s in average daily traffic ( ADT ) under CA Vs 17 scenario in the road network of Chicago metropolitan area as the dependent variable of the model. 18 Second, a comprehensive set of variable s and indicators representing network characteristics and 19 urban structure patterns are generated. Three machine learning models namely K-Nearest 20 neighbors , Random Forest , and eXtreme Gradient Boosting are developed and validated to 21 establish the relationship between network characteri stics and change s in ADT under CA Vs 22 scenario . The estimated models are found to yield acceptable performance . In addition, SHapley 23 Additive exPlanations (SHAP) analysis tool is employed to investigate the impact of important 24 features on changes in ADT , which discloses the most important link properties, network features , 25 and demographic information in predicting change in ADT under the analyzed CA Vs scenario . 26 27 Keywords : Connected and Autonomous Vehicle s, POLARIS , Traffic Flow , Machine Learning 28 1. Introduction 29 Emergence of the c onnected and a utonomous vehicles (CAVs) is a controversial topic in 30 transportation community since they are expected to revolutionize both human mobility and goods 31 transport in near future. In the United Sta tes, it is predicted that penetration of CAVs in light -duty- 32 vehicle fleet will be up to 24.8% by the year 2045, if the technology price annually drops by 5% , 33 and Americans’ willingness to pay (WTP) increases by 5% in each year (1). Accordingly, with 34 10% annual price reductions and WTP increase s, penetration of CAVs can reach up to 87.2% (1). 35 It is also reported in a nother study that , if CAVs prices decrease at rates of 15% or 20% per year, 36 it is expected that their market share will be homogeneous and near 100% by the year 2050 (2). 37 1 Corresponding author. Tel: +1 (312) 996 -9840. Email addresses : aparsa2@uic.edu (A. B. Parsa), rshaba4@uic.edu (R. Shabanpour), kouros@uic.edu (A. K. Mohammadian) , jauld@anl.gov (J. Auld), tstephens@anl.gov (T. Stephens) . 2 Aligned wit h the rapid technological advancements in this area, m ost of major car companies have 38 announced that they will release their fully autonomous vehicles in the next decade (3, 4). 39 Given that CAVs have the potential to substitute the current vehicle fleet (5), a growing 40 number of studies have focused on evaluat ing the impact of this new technolog y on different 41 aspects of transportation systems . One aspect that is expected to be substantially affected by 42 emergence this technology is travel demand (6). It is predicted that an AV fleet size of only one - 43 third the number of private vehicles would be enough to meet the demand generated today (7). 44 Potential change in peoples’ p
The purpose of the paper is to guide engineering students and ease their transition from the most basic DC-DC converter topologies to more advanced types. The buck, boost and buck-boost converters are the usual suspects in textbooks and engineering classes to introduce students to the basics of power electronics and switch mode power supplies. There is a gap of how detailed such second order DC-DC converters are described and the more advanced fourth order such as theCuk, Zeta and Single-Ended Primary-Inductor Converter (SEPIC). This paper gives a detailed derivation of the equations governing the SEPIC. An example of sizing of components is presented for a range of input voltages and power levels. Finally the design is veri ed by a circuit simulation using LTSpice. 1 Introduction Engineering students are introduced to the topics of power electronics and switch mode power supplies through the derivation of the simple second order DC-DC converter topologies such as the buck, boost and buck-boost. The operation of such converters is described in detail and the governing equations are derived step by step in various text books and freely available online sources. However, there is a steep learning curve in open access knowledge when it comes to expanding this knowledge further to fourth order DC-DC converter types such as the Cuk, Zeta and Single-Ended Primary-Inductor Converter (SEPIC) topologies. The SEPIC is used as the primary case of study for this paper. Often in literature the SEPIC is brie y described and nal equations for design are presented with little information of how the equations were originally derived [1 {6]. While these
The incipient motion process of settled particle s in supercritical CO 2 was studied through experimental mea surements and force analyses. By referring to the theories of sand -wind and sediment restarting, the incipient motion state descripti on and mechanism were optimized to fill the theoretical ga ps in particle restarting research in the petroleum industry. Visualization experiments were carried out under various temperature, pressure , and particle conditions. The critical pump rates for the onset of grain motion in supercritical CO 2 were measured . A critical pump rate empirical formula was obtained based on the experimental results and a derived Shields number expression. The average critical Shields number in supercritical CO 2 was 0.00 28. The cohesive force on particle s is zero in supercritical CO 2 based on its non-interfacial -tension characteristic . The measured spinning rate of the restarting particle s in supercritical CO 2 was 121 r/s on average. Therefore , the calculated value of the Magnus f orce was approximately 30% of the force of gravity on particle . Particle incipient motion in supercritical CO 2 has a varying driving force ( Magnus force) and simple resistant force ( lack of cohesive force) , which enhances the incipient motion of particle s in supercritical CO 2. Keywords: supercritical CO 2; particle incipient motion; visualization experiments; Shields number; Magnus force *Manuscript Click here to view linked
Theauthorpresentsanoveldesignofminingasteroidsinzerogravitythatis moreefficientthanpresentconceptsasitleavesunwantedmaterialsandunlocks potentialtocomebackwithrefinedminerals. Keywords Mistmining,ZeroGravity,Abrasive,Refining. Introduction Presentmachinedesignforminingasteroidsincludemethodssuchasscraping, drilling,heating,cooling,bendingandmanymoreanditmustbenotedthatinall themethodsmentionedmistformationmustbeavoided.Thisparticulardesign presentedusesmistformationmethodtominetheasteroidinonegoanduses designpresentedinpapertitled,"Spacestructuredesignforrefiningmineralsin zerogravity”[1]forrefinement.Astepbystepinnovationcanbeseeninthe failedattemptdepictedbelow.Dimensionallibertieshavebeentaken. FailedConcept Figure1 Infigure1,thedesignutilizes4structures:Funnelintegratedwithhelical protrudings(blue),abrasiveminingmechanism(red),collectionandtranslation tube(grey),gaspassagewithintegratedcompressor/suction-erandfilter.The designfailedduetothefactthatgaswillpushfunnelawayfromasteroid. InnovatedDesign Figure2 Infigure2,thehelicalprotrudingshavebeenreplacedwithflapstopushthemist insidethecone. Conclusion/Remarks Thecollectionefficiencyhasbeengreatlyimprovednotuponthefailedattempt, uponexistingmethodsandwhencombinedwithzerogravityrefiner,thevessel canreturnwithmuchsuccessthanotheravailablemethodsasauthor’s knowledge.Topologyoptimizationisneededandontheouterrimofcone, sorbothaneissuggestedforkeepingafirmgriponasteroidsurfacewithmuch neededforce,themicro-modulesofthesedesignandtheonereferencedshould alsobeconceptualizedtofurtherinnovateforefficiency.Itmustbenotedthat theflapsmotionmustbeinaccordancetodensityandnotconstantascanbe seeninatmosphereonearthasageneralizedobservatoryfactthatthemotionof mostbirdsglidingandhoneybeeflappingismostlyduetotheeffectof surroundingairmoleculesandtheirrespectiveconcentrationaroundthesurface ofwingsandlessbecauseofweightofbirdsthemselves.Thebird’swingsfeel fluid(air)lessdensethantheinsects,that’swhytherowingactionismore prominentininsect’swingmotion.
In the experiment underlying the St. Petersburg paradox, we use state-dependent linear utility functions for money with a countably infinite set of states of nature to show that a potential participant will be willing to pay no more than a finite sum of money to participate in the experiment. Keywords : St. Petersburg paradox, countably infinite states of nature, state-dependent linear utility function of money 1. Introduction The conventional statement of the St. Petersburg paradox (see for instance page 4 in Chapter 1 of Biswas (1997)) goes something like the following: In an experiment consisting of independent tosses of an unbiased coin, a participant receives 2n units of money if the first head occurs on the nth toss. How much should one be willing to pay for participating in the experiment? “The problem was invented by Nicolas Bernoulli (1687- 1759) who stated it in a letter to Pierre Raymond de Montmort (1678- 1719) on September 9, 1713. However, the paradox takes its name from its analysis by Nicolas' cousin Daniel Bernoulli (1700-1782), one-time resident of Saint Petersburg , who in 1738 published his thoughts about the problem in the Commentaries of the Imperial Academy of Science of Saint Petersburg” . (https://en.wikipedia.org/wiki/St._Petersburg_paradox ). It is important to note that the genesis of the paradox, suggests that none of the three mathematicians mentioned above were familiar with the work of the statistician and philosopher Thomas Bayes (1701- 1761) at the time of their correspondence. The standard conclusion based on the above experiment is that if the utility function for monetary returns was strictly increasing and linear, then since ∑2௡(ଵ ଶ)௡  ௡ୀଵ = +, there should be no upper bound on what a participant would be willing to pay to participate in the experiment, contrary to what would be expected in reality. In reality, no one would be willing to pay more than some finite amount of money to participate in the experiment. Hence, this could be construed as an argument against strictly increasing and linear utility function for money (i.e., individuals being risk neutral) and therefore an argument in favour of a utility function for money which is non-linear, such as the natural logarithm of money. In 1728, a mathematician from Geneva- Gabriel Cramer (1704- 1752)- in a private communication suggested that there is a saturation level for the utility money, beyond which its utility or use value remains constant. This could be the idea that motivated the use of utility functions for wealth that are strictly concave, strictly increasing but bounded above (e.g. u(x) = a- ae-x for some positive real number ‘a’). Much work and discussion has taken place on this topic and a comprehensive survey of the same may be found in Gasparian, Kiseleva, Korneev, Lebedev and Lebedev (2018), Peterson (2023) and
This paper reports on a study of the damage tolerance of carbon fibre re- inforced polymer plates, used in aircraft fuselage, subjected to multi-site impacts. A new fixture was designed to perform sequential low-velocity im- pacts at different locations on plates with two different thicknesses, represent- ing upper and lower fuselage panels. The residual strength in compression was measured using a new compression-after-impact rig designed to prevent global buckling of thin plates. Experimental results indicated that compared to single impacts, multi-site impacts can reduce the residual strength of the thin plates, but not the thick plates. To explain this difference, a detailed finite element model was developed, which enabled modelling of multi-site impacts and compression after impact in one simulation. Simulations sug- gested that the second impact damage changes the buckled shape prior to failure for the thin plates. A parametric analysis on key material parameters showed that they have a small effect on the residual compressive strength. This work can help to improve the design of aircraft panels with respect to ∗Corresponding author Email address: spsarras@upatras.gr (Spyridon Psarras) Preprint submitted to Elsevier January 20, 2023Manuscript File Click here to view linked
This study explores the complexities of Mixed Income Housing (MIH) development in South Africa within the context of the United Nations Sustainable Development Goal 11, which aims to create inclusive, safe, resilient, and sustainable cities. It develops th e Equitable Urban Investment Theory (EUIT), integrating principles from investment theory, social equity, and New Urbanism, to provide a holistic approach to MIH. Employing a qualitative research methodology, including semi -structured interviews, site visits, and the Delphi method, the research identiﬁes six thematic insights that inform strategic guidelines for sustainable MIH development. Key ﬁndings highlight the viability of MIH without legislative mandates, emphasizing the role of Public -Private Part nerships (PPPs) and community -based collaborations in overcoming challenges such as NIMBYism and ﬁnancial constraints. The study critiques traditional investment theory for its narrow focus on ﬁnancial aspects, advocating for a broader approach that includes social outcomes such as community development and social inclusion. By integrating social justice and New Urbanism principles, the EUIT framework balances economic viability with the imperative for social equity and sustainable urban planning. The rec ommendations advocate for repositioning MIH as an investment asset, supported by government- provided land and infrastructure, to facilitate the inclusion of low -income units. The research concludes that sustainable MIH developments require a multifaceted a pproach that aligns policy, investment, and community objectives, promoting urban integration and socio- economic dynamism. These ﬁndings provide a roadmap for policymakers, developers, and urban planners to advance inclusive and sustainable urban housing solutions in South Africa and similar contexts globally. Keywords: Green Technologies, Inclusive Urban Development, Public -Private Partnerships, Sustainable Housing, Urban Policy. PREPRINT – 09/06/2024 – VERSION 2 – CC BY -SA 4.0 DEED – SUBMITTED TO THE JOURNAL OF HOUSING ECONOMICS WITH A WORD COUNT OF: 9,655 (JOURNAL ACCEPTANCE RATE – UNKNOWN % AT TIME OF SUBMISSION) Page 2 of 33 Word Count: Original Manuscript ( 9,655), this submission does not relate to a conference or a special issue . (Word count excludes title, author names and afﬁliations, abstract, keywords, highlights, abbreviations, table/ﬁgure captions, acknowledgments, and
The properties of b utanol offer more promising results compared to those of lower chain alcohol such as methanol or ethanol. However, butanol as a biofuel has not yet been commercially produced due to its costly process. Butanol is gener ally produced via the process of Acetone -Butanol -Ethanol (ABE ) fermentation and can only be acquired after it was recovered from the ABE solvent . Despite the eff orts and recent developments, obtaining higher butanol concentration from ABE fermentation is still relatively expensive and challenging . The ide a of using ABE directly in internal combustion engines is then proposed to eliminate the recovery process . Seve ral preliminary studies have reported several promising results of using ABE blends in both gasoline and diesel engines. However, researches in t his area are still in the early stages , and thorough investigations are required. This review paper aims to provide essential findings from the latest development in the addition of ABE both with gasoline and diesel fuel in Spark Ignition (SI) and Compress ion Ignition (CI) engines. A brief discussion on ABE properties will be firstly given before the effects of its addition on SI and CI engine is comprehensively reviewed. The end of this article highlights some possible contributions and research gaps . Keywords: butanol; biofuel; acetone -butanol -ethanol (ABE); gasoline; diesel, SI, CI 1. Introduction ................................ ................................ ................................ ................................ .. 2 2. ABE properties ................................ ................................ ................................ .............................. 5 3. ABE addition in gasoline engine ................................ ................................ ................................ .... 8 3.1 Performance ................................ ................................ ................................ ........................... 8 3.2 Combustion ................................ ................................ ................................ ........................... 13 4. ABE addition in diesel engine ................................ ................................ ................................ ...... 17 4.1 Performance ................................ ................................ ................................ ......................... 17 4.2 Spray and combustion ................................ ................................ ................................ ........... 27 4.3 Emission ................................ ................................ ................................ ................................ 30 5. Research gaps ................................ ................................ ................................ ............................. 38 Acknowledgment ................................ ................................ ................................ ............................ 39